Read the Docs build information
Build id: 2353615
Project: datarobot-public-api-client
Version: v3.5.0
Commit: f12ef43d473ddccb9901ac03192901e06bb80932
Date: 2024-07-16T23:29:20.982778Z
State: finished
Success: True


[rtd-command-info] start-time: 2024-07-16T23:29:22.225525Z, end-time: 2024-07-16T23:29:25.229318Z, duration: 3, exit-code: 0
git clone --depth 1 git@github.com:datarobot/public_api_client.git .
Cloning into '.'...
Warning: Permanently added 'github.com' (ED25519) to the list of known hosts.

[rtd-command-info] start-time: 2024-07-16T23:29:25.334013Z, end-time: 2024-07-16T23:29:26.770075Z, duration: 1, exit-code: 0
git fetch origin --force --prune --prune-tags --depth 50 refs/tags/v3.5.0:refs/tags/v3.5.0
Warning: Permanently added 'github.com' (ED25519) to the list of known hosts.
From github.com:datarobot/public_api_client
 * [new tag]         v3.5.0         -> v3.5.0
 * [new tag]         latest-release -> latest-release

[rtd-command-info] start-time: 2024-07-16T23:29:26.902074Z, end-time: 2024-07-16T23:29:27.571187Z, duration: 0, exit-code: 0
git checkout --force f12ef43d473ddccb9901ac03192901e06bb80932
Note: switching to 'f12ef43d473ddccb9901ac03192901e06bb80932'.

You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by switching back to a branch.

If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -c with the switch command. Example:

  git switch -c <new-branch-name>

Or undo this operation with:

  git switch -

Turn off this advice by setting config variable advice.detachedHead to false

HEAD is now at f12ef43 bump sdk version to 3.5.0 (#3205)

[rtd-command-info] start-time: 2024-07-16T23:29:27.643424Z, end-time: 2024-07-16T23:29:27.704538Z, duration: 0, exit-code: 0
cat .readthedocs.yml
# .readthedocs.yml
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details

# Required
version: 2

# Build documentation in the docs/ directory with Sphinx
sphinx:
  configuration: sdk_docs/conf.py

# Build documentation with MkDocs
#mkdocs:
#  configuration: mkdocs.yml

# Optionally build your docs in additional formats such as PDF
formats:
  - pdf

# Optionally set the version of Python and requirements required to build your docs
python:
  install:
    - method: pip
      path: .
      extra_requirements:
        - dev

build:
  os: ubuntu-22.04
  tools:
    python: "3.8"

[rtd-command-info] start-time: 2024-07-16T23:29:33.715890Z, end-time: 2024-07-16T23:29:33.802208Z, duration: 0, exit-code: 0
asdf global python 3.8.19


[rtd-command-info] start-time: 2024-07-16T23:29:34.210931Z, end-time: 2024-07-16T23:29:35.535337Z, duration: 1, exit-code: 0
python -mvirtualenv $READTHEDOCS_VIRTUALENV_PATH
created virtual environment CPython3.8.19.final.0-64 in 962ms
  creator CPython3Posix(dest=/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0, clear=False, no_vcs_ignore=False, global=False)
  seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/home/docs/.local/share/virtualenv)
    added seed packages: pip==23.1, setuptools==67.6.1, wheel==0.40.0
  activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator

[rtd-command-info] start-time: 2024-07-16T23:29:35.616738Z, end-time: 2024-07-16T23:29:47.038165Z, duration: 11, exit-code: 0
python -m pip install --upgrade --no-cache-dir pip setuptools
Requirement already satisfied: pip in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages (23.1)
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Requirement already satisfied: setuptools in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages (67.6.1)
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Installing collected packages: setuptools, pip
  Attempting uninstall: setuptools
    Found existing installation: setuptools 67.6.1
    Uninstalling setuptools-67.6.1:
      Successfully uninstalled setuptools-67.6.1
  Attempting uninstall: pip
    Found existing installation: pip 23.1
    Uninstalling pip-23.1:
      Successfully uninstalled pip-23.1
Successfully installed pip-24.1.2 setuptools-70.3.0

[rtd-command-info] start-time: 2024-07-16T23:29:47.118711Z, end-time: 2024-07-16T23:29:59.805580Z, duration: 12, exit-code: 0
python -m pip install --upgrade --no-cache-dir sphinx readthedocs-sphinx-ext
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Installing collected packages: snowballstemmer, pytz, zipp, urllib3, sphinxcontrib-serializinghtml, sphinxcontrib-qthelp, sphinxcontrib-jsmath, sphinxcontrib-htmlhelp, sphinxcontrib-devhelp, sphinxcontrib-applehelp, Pygments, packaging, MarkupSafe, imagesize, idna, docutils, charset-normalizer, certifi, babel, alabaster, requests, Jinja2, importlib-metadata, sphinx, readthedocs-sphinx-ext
Successfully installed Jinja2-3.1.4 MarkupSafe-2.1.5 Pygments-2.18.0 alabaster-0.7.13 babel-2.15.0 certifi-2024.7.4 charset-normalizer-3.3.2 docutils-0.20.1 idna-3.7 imagesize-1.4.1 importlib-metadata-8.0.0 packaging-24.1 pytz-2024.1 readthedocs-sphinx-ext-2.2.5 requests-2.32.3 snowballstemmer-2.2.0 sphinx-7.1.2 sphinxcontrib-applehelp-1.0.4 sphinxcontrib-devhelp-1.0.2 sphinxcontrib-htmlhelp-2.0.1 sphinxcontrib-jsmath-1.0.1 sphinxcontrib-qthelp-1.0.3 sphinxcontrib-serializinghtml-1.1.5 urllib3-2.2.2 zipp-3.19.2

[rtd-command-info] start-time: 2024-07-16T23:29:59.889610Z, end-time: 2024-07-16T23:30:50.793259Z, duration: 50, exit-code: 0
python -m pip install --upgrade --upgrade-strategy only-if-needed --no-cache-dir .[dev]
Processing /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
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Building wheels for collected packages: datarobot, jupyter-contrib-nbextensions, jupyter_contrib_core
  Building wheel for datarobot (pyproject.toml): started
  Building wheel for datarobot (pyproject.toml): finished with status 'done'
  Created wheel for datarobot: filename=datarobot-3.5.0-py3-none-any.whl size=1058232 sha256=918e5c989f8f3f9ea70bd1a969b2bb37efc5581b2f0c57740988f16e50244f87
  Stored in directory: /tmp/pip-ephem-wheel-cache-84ajc1e0/wheels/d7/91/d9/318a45d59f1cba5379d3d30d294e14b42132b4bbca67a875aa
  Building wheel for jupyter-contrib-nbextensions (setup.py): started
  Building wheel for jupyter-contrib-nbextensions (setup.py): finished with status 'done'
  Created wheel for jupyter-contrib-nbextensions: filename=jupyter_contrib_nbextensions-0.7.0-py2.py3-none-any.whl size=23428778 sha256=3bf5341024c692089920428dce6a7d5d8c348635cbceeb613d24b2b28579e3d8
  Stored in directory: /tmp/pip-ephem-wheel-cache-84ajc1e0/wheels/1a/60/9f/043697d3cd00df43b23bbf4e722366a2abfa68700b6d8411f4
  Building wheel for jupyter_contrib_core (setup.py): started
  Building wheel for jupyter_contrib_core (setup.py): finished with status 'done'
  Created wheel for jupyter_contrib_core: filename=jupyter_contrib_core-0.4.2-py2.py3-none-any.whl size=17480 sha256=68c00ab162ef823ae315d856b79a8c5eb6e0dafbddb23ca2cc6b0433d385a1fb
  Stored in directory: /tmp/pip-ephem-wheel-cache-84ajc1e0/wheels/c5/75/d2/b881eea79157be355b125d974ec85f88d6e6742acd14387872
Successfully built datarobot jupyter-contrib-nbextensions jupyter_contrib_core
Installing collected packages: webencodings, wcwidth, types-urllib3, types-PyYAML, types-pytz, types-python-dateutil, trafaret, strenum, py4j, pure-eval, ptyprocess, pickleshare, jupyter_highlight_selected_word, ipython_genutils, fastjsonschema, backcall, wrapt, websocket-client, webcolors, urllib3, uri-template, tzdata, typing-extensions, types-requests, traitlets, tornado, tomlkit, tomli, tokenize-rt, tinycss2, soupsieve, sniffio, six, send2trash, rpds-py, rfc3986-validator, pyzmq, pyyaml, python-json-logger, pyflakes, pyenchant, pycparser, pycodestyle, pyasn1, py, psutil, protobuf, prompt-toolkit, prometheus-client, pluggy, platformdirs, pkgutil-resolve-name, Pillow, pexpect, pathspec, parso, pandocfilters, overrides, numpy, nest-asyncio, mypy-extensions, mistune, mccabe, lxml, lazy-object-proxy, jupyterlab-pygments, jsonpointer, json5, isort, iniconfig, importlib-resources, h11, grpcio, fqdn, executing, exceptiongroup, docutils, dill, defusedxml, decorator, debugpy, coverage, click, cachetools, attrs, terminado, rsa, rfc3339-validator, referencing, python-dateutil, pytest, pyasn1-modules, pyarrow, mypy, matplotlib-inline, jupyter_core, jedi, httpcore, googleapis-common-protos, flake8, comm, cffi, bleach, black, beautifulsoup4, async-lru, asttokens, astroid, anyio, stack-data, sphinx, responses, requests-toolbelt, pytest-cov, pytest-asyncio, pylint, pandas, jupyter-server-terminals, jupyter-client, jsonschema-specifications, httpx, grpcio-status, google-auth, arrow, argon2-cffi-bindings, sphinxcontrib-spelling, sphinx-rtd-theme, sphinx-autodoc-typehints, numpydoc, jsonschema, isoduration, ipython, datarobot, databricks-sdk, argon2-cffi, nbformat, ipykernel, databricks-connect, nbclient, jupyter-events, nbconvert, nbsphinx, jupyter-server, notebook-shim, jupyterlab-server, jupyter-lsp, jupyterlab, notebook, jupyter_contrib_core, jupyter_nbextensions_configurator, jupyter-contrib-nbextensions
  Attempting uninstall: urllib3
    Found existing installation: urllib3 2.2.2
    Uninstalling urllib3-2.2.2:
      Successfully uninstalled urllib3-2.2.2
  Attempting uninstall: docutils
    Found existing installation: docutils 0.20.1
    Uninstalling docutils-0.20.1:
      Successfully uninstalled docutils-0.20.1
  Attempting uninstall: sphinx
    Found existing installation: Sphinx 7.1.2
    Uninstalling Sphinx-7.1.2:
      Successfully uninstalled Sphinx-7.1.2
Successfully installed Pillow-9.2.0 anyio-4.4.0 argon2-cffi-23.1.0 argon2-cffi-bindings-21.2.0 arrow-1.3.0 astroid-2.13.5 asttokens-2.4.1 async-lru-2.0.4 attrs-23.2.0 backcall-0.2.0 beautifulsoup4-4.12.3 black-23.1.0 bleach-6.1.0 cachetools-5.4.0 cffi-1.16.0 click-8.1.7 comm-0.2.2 coverage-7.6.0 databricks-connect-13.0.1 databricks-sdk-0.29.0 datarobot-3.5.0 debugpy-1.8.2 decorator-5.1.1 defusedxml-0.7.1 dill-0.3.8 docutils-0.17.1 exceptiongroup-1.2.2 executing-2.0.1 fastjsonschema-2.20.0 flake8-5.0.4 fqdn-1.5.1 google-auth-2.32.0 googleapis-common-protos-1.63.2 grpcio-1.64.1 grpcio-status-1.64.1 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 importlib-resources-6.4.0 iniconfig-2.0.0 ipykernel-6.29.5 ipython-8.12.3 ipython_genutils-0.2.0 isoduration-20.11.0 isort-5.10.1 jedi-0.19.1 json5-0.9.25 jsonpointer-3.0.0 jsonschema-4.23.0 jsonschema-specifications-2023.12.1 jupyter-client-8.6.2 jupyter-contrib-nbextensions-0.7.0 jupyter-events-0.10.0 jupyter-lsp-2.2.5 jupyter-server-2.14.2 jupyter-server-terminals-0.5.3 jupyter_contrib_core-0.4.2 jupyter_core-5.7.2 jupyter_highlight_selected_word-0.2.0 jupyter_nbextensions_configurator-0.6.4 jupyterlab-4.2.3 jupyterlab-pygments-0.3.0 jupyterlab-server-2.27.3 lazy-object-proxy-1.10.0 lxml-5.2.2 matplotlib-inline-0.1.7 mccabe-0.7.0 mistune-3.0.2 mypy-1.0.0 mypy-extensions-1.0.0 nbclient-0.10.0 nbconvert-7.16.4 nbformat-5.10.4 nbsphinx-0.8.9 nest-asyncio-1.6.0 notebook-7.2.1 notebook-shim-0.2.4 numpy-1.24.4 numpydoc-1.4.0 overrides-7.7.0 pandas-2.0.3 pandocfilters-1.5.1 parso-0.8.4 pathspec-0.12.1 pexpect-4.9.0 pickleshare-0.7.5 pkgutil-resolve-name-1.3.10 platformdirs-4.2.2 pluggy-1.5.0 prometheus-client-0.20.0 prompt-toolkit-3.0.47 protobuf-5.27.2 psutil-6.0.0 ptyprocess-0.7.0 pure-eval-0.2.2 py-1.11.0 py4j-0.10.9.7 pyarrow-16.1.0 pyasn1-0.6.0 pyasn1-modules-0.4.0 pycodestyle-2.9.1 pycparser-2.22 pyenchant-3.2.2 pyflakes-2.5.0 pylint-2.15.0 pytest-7.1.2 pytest-asyncio-0.21.1 pytest-cov-5.0.0 python-dateutil-2.9.0.post0 python-json-logger-2.0.7 pyyaml-6.0.1 pyzmq-26.0.3 referencing-0.35.1 requests-toolbelt-1.0.0 responses-0.21.0 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 rpds-py-0.19.0 rsa-4.9 send2trash-1.8.3 six-1.16.0 sniffio-1.3.1 soupsieve-2.5 sphinx-5.3.0 sphinx-autodoc-typehints-1.17.1 sphinx-rtd-theme-1.0.0 sphinxcontrib-spelling-8.0.0 stack-data-0.6.3 strenum-0.4.15 terminado-0.18.1 tinycss2-1.3.0 tokenize-rt-5.2.0 tomli-2.0.1 tomlkit-0.13.0 tornado-6.4.1 trafaret-2.1.1 traitlets-5.14.3 types-PyYAML-6.0.12 types-python-dateutil-2.8.19 types-pytz-2022.2.1.0 types-requests-2.28.11 types-urllib3-1.26.25 typing-extensions-4.12.2 tzdata-2024.1 uri-template-1.3.0 urllib3-1.26.19 wcwidth-0.2.13 webcolors-24.6.0 webencodings-0.5.1 websocket-client-1.8.0 wrapt-1.16.0

[rtd-command-info] start-time: 2024-07-16T23:30:51.694589Z, end-time: 2024-07-16T23:30:51.757199Z, duration: 0, exit-code: 0
cat sdk_docs/conf.py
#
# Copyright 2021 DataRobot, Inc. and its affiliates.
#
# All rights reserved.
#
# DataRobot, Inc.
#
# This is proprietary source code of DataRobot, Inc. and its
# affiliates.
#
# Released under the terms of DataRobot Tool and Utility Agreement.
#
# DataRobot Python API documentation build configuration file, created by
# sphinx-quickstart on Mon Mar 16 10:50:19 2015.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import os
import shutil
import sys
from zipfile import ZipFile

import sphinx_rtd_theme

sys.path.insert(0, os.path.abspath(".."))
from datarobot import __version__ as version  # noqa

# Make sure magic 'tags' field is defined.
# (Not actually useful but makes Cython and pylint errors go away.)
if "tags" not in locals():
    tags = None
if "b" in version:
    # mainline quarterly releases never have the beta "b" in the version, only internal & weekly do
    tags.add("include_experimental_docs")

# Copy the changelog to the docs directory so sphinx will include it
root_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
changelog_path = os.path.join(root_dir, "CHANGES.rst")
dest_path = os.path.join(root_dir, "sdk_docs", "CHANGES.rst")
assert os.path.isfile(changelog_path)
shutil.copyfile(changelog_path, dest_path)

# Create a zip file of the example resources (csv, py, ipynb)
# so that it can be included it as a download within the HTML docs
files_to_zip = []
for root, _, files in os.walk("examples"):
    basename = os.path.basename(root)
    # skip "hidden" directories like notebook autosaves and _build
    if not basename.startswith("_") and not basename.startswith("."):
        for file in files:
            name, ext = os.path.splitext(file)
            ext_lower = ext.lower()
            if ext_lower in [".csv", ".xls", ".xlsx", ".ipynb", ".py"]:
                files_to_zip.append(os.path.join(root, file))
with ZipFile("datarobot_examples.zip", "w") as examples_zip:
    for file in files_to_zip:
        examples_zip.write(file)

# -- General configuration -----------------------------------------------------

# If your documentation needs a minimal Sphinx version, state it here.
# needs_sphinx = '1.0'

# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = [
    "sphinxcontrib.spelling",
    "sphinx.ext.autodoc",
    "sphinx.ext.autosummary",
    "sphinx.ext.doctest",
    "numpydoc",
    "nbsphinx",
    "sphinx_autodoc_typehints",
]

# make warnings go away- as advised by
# https://github.com/phn/pytpm/issues/3#issuecomment-12133978
numpydoc_show_class_members = False

nbsphinx_execute = "never"

# Add any paths that contain templates here, relative to this directory.
templates_path = ["_templates"]

# The suffix of source filenames.
source_suffix = ".rst"

# Showing automatically documented members in same order as they are in source
autodoc_member_order = "bysource"

# The encoding of source files.
# source_encoding = 'utf-8-sig'

# The master toctree document.
master_doc = "index"

# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# Thes are both the full X.Y.Z version, including alpha/beta/rc tags.
# We think Sphinx probably wants both to be defined.
release = version

project = "DataRobot Python Client"
copyright = "2019, DataRobot, Inc"


# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
# language = None

# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
# today = ''
# Else, today_fmt is used as the format for a strftime call.
# today_fmt = '%B %d, %Y'

# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ["_build", "**/.ipynb_checkpoints"]

# The reST default role (used for this markup: `text`) to use for all documents.
# default_role = None

# If true, '()' will be appended to :func: etc. cross-reference text.
# add_function_parentheses = True

# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
# add_module_names = True

# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
# show_authors = False

# The name of the Pygments (syntax highlighting) style to use.
pygments_style = "sphinx"

# A list of ignored prefixes for module index sorting.
# modindex_common_prefix = []


# -- Options for HTML output ---------------------------------------------------

# The theme to use for HTML and HTML Help pages.  See the documentation for
# a list of builtin themes.

html_theme = "sphinx_rtd_theme"
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]

# Theme options are theme-specific and customize the look and feel of a theme
# further.  For a list of options available for each theme, see the
# documentation.
# html_theme_options = {}

# Add any paths that contain custom themes here, relative to this directory.
# html_theme_path = []

# The name for this set of Sphinx documents.  If None, it defaults to
# "<project> v<release> documentation".
# html_title = None

# A shorter title for the navigation bar.  Default is the same as html_title.
# html_short_title = None

# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
# html_logo = None

# The name of an image file (within the static path) to use as favicon of the
# docs.  This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
# html_favicon = None

# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ["_static"]
html_extra_path = ["_html"]

# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
# html_last_updated_fmt = '%b %d, %Y'

# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
# html_use_smartypants = True

# Custom sidebar templates, maps document names to template names.
# html_sidebars = {}

# Additional templates that should be rendered to pages, maps page names to
# template names.
# html_additional_pages = {}

# If false, no module index is generated.
# html_domain_indices = True

# If false, no index is generated.
# html_use_index = True

# If true, the index is split into individual pages for each letter.
# html_split_index = False

# If true, links to the reST sources are added to the pages.
# html_show_sourcelink = True

# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
# html_show_sphinx = True

# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
# html_show_copyright = True

# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it.  The value of this option must be the
# base URL from which the finished HTML is served.
# html_use_opensearch = ''

# This is the file name suffix for HTML files (e.g. ".xhtml").
# html_file_suffix = None

# Output file base name for HTML help builder.
htmlhelp_basename = "DataRobotPythonDoc"


# -- Options for LaTeX output --------------------------------------------------

# latex_elements = {
#     The paper size ('letterpaper' or 'a4paper').
#     'papersize': 'letterpaper',

#     The font size ('10pt', '11pt' or '12pt').
#     'pointsize': '10pt',

#     Additional stuff for the LaTeX preamble.
#     'preamble': '',
# }

fh = open("latex_preamble.tex", "r+")
PREAMBLE = fh.read()
fh.close()
latex_elements = {
    "inputenc": "",
    "utf8extra": "",
    "preamble": PREAMBLE,
}

# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title, author, documentclass [howto/manual]).
latex_documents = [
    (
        "index",
        f"DataRobotPython_{version}_Docs.tex",
        "DataRobot Python API Documentation",
        "DataRobot, Inc.",
        "manual",
    ),
]

# The name of an image file (relative to this directory) to place at the top of
# the title page.
# latex_logo = None

# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
# latex_use_parts = False

# If true, show page references after internal links.
# latex_show_pagerefs = False

# If true, show URL addresses after external links.
# latex_show_urls = False

# Documents to append as an appendix to all manuals.
# latex_appendices = []

# If false, no module index is generated.
# latex_domain_indices = True


# -- Options for manual page output --------------------------------------------

# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
    ("index", "datarobotpython", "DataRobot Python API Documentation", ["DataRobot, Inc."], 1)
]

# If true, show URL addresses after external links.
# man_show_urls = False


# -- Options for Texinfo output ------------------------------------------------

# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
#  dir menu entry, description, category)
texinfo_documents = [
    (
        "index",
        "DataRobotPython",
        "DataRobot Python API Documentation",
        "DataRobot, Inc.",
        "DataRobotPython",
        "One line description of project.",
        "Miscellaneous",
    ),
]

# Documents to append as an appendix to all manuals.
# texinfo_appendices = []

# If false, no module index is generated.
# texinfo_domain_indices = True

# How to display URL addresses: 'footnote', 'no', or 'inline'.
# texinfo_show_urls = 'footnote'

# Nitpick targets to ignore:
# These are third-party packages that don't expose documentation for sphinx to link

nitpick_ignore = [
    ("py:data", "typing.Tuple"),
    ("py:data", "typing.Optional"),
    ("py:data", "typing.Union"),
    ("py:data", "typing.NoReturn"),
    ("py:data", "typing.Any"),
    ("py:class", "pandas.core.frame.DataFrame"),
    ("py:class", "requests.models.Response"),
    ("py:class", "datetime.datetime"),
    ("py:class", "PIL.Image.Image"),
    ("py:class", "collections.OrderedDict"),
]

# options for spelling
spelling_ignore_contributor_names = False
spelling_add_pypi_package_names = True
spelling_ignore_importable_modules = True
spelling_ignore_python_builtins = True
spelling_ignore_wiki_words = True
spelling_filters = [
    "sdk_docs.spelling_filters.filters.DocstringFilePathFilter",
    "sdk_docs.spelling_filters.filters.TypeAnnotationFilter",
    "sdk_docs.spelling_filters.filters.CamelCaseFilter",
    "sdk_docs.spelling_filters.filters.SortOrderFilter",
    "sdk_docs.spelling_filters.filters.OrdinalFilter",
    "sdk_docs.spelling_filters.filters.ObjectIdFilter",
    "sdk_docs.spelling_filters.filters.DayMonthFilter",
    "sdk_docs.spelling_filters.filters.DataRobotParameterFilter",
]


def setup(app):
    app.add_css_file("css/tight_table.css")




###########################################################################
#          auto-created readthedocs.org specific configuration            #
###########################################################################


#
# The following code was added during an automated build on readthedocs.org
# It is auto created and injected for every build. The result is based on the
# conf.py.tmpl file found in the readthedocs.org codebase:
# https://github.com/rtfd/readthedocs.org/blob/main/readthedocs/doc_builder/templates/doc_builder/conf.py.tmpl
#
# Note: this file shouldn't rely on extra dependencies.

import importlib
import sys
import os.path

# Borrowed from six.
PY3 = sys.version_info[0] == 3
string_types = str if PY3 else basestring

from sphinx import version_info

# Get suffix for proper linking to GitHub
# This is deprecated in Sphinx 1.3+,
# as each page can have its own suffix
if globals().get('source_suffix', False):
    if isinstance(source_suffix, string_types):
        SUFFIX = source_suffix
    elif isinstance(source_suffix, (list, tuple)):
        # Sphinx >= 1.3 supports list/tuple to define multiple suffixes
        SUFFIX = source_suffix[0]
    elif isinstance(source_suffix, dict):
        # Sphinx >= 1.8 supports a mapping dictionary for multiple suffixes
        SUFFIX = list(source_suffix.keys())[0]  # make a ``list()`` for py2/py3 compatibility
    else:
        # default to .rst
        SUFFIX = '.rst'
else:
    SUFFIX = '.rst'

# Add RTD Static Path. Add to the end because it overwrites previous files.
if not 'html_static_path' in globals():
    html_static_path = []
if os.path.exists('_static'):
    html_static_path.append('_static')

# Define this variable in case it's not defined by the user.
# It defaults to `alabaster` which is the default from Sphinx.
# https://www.sphinx-doc.org/en/master/usage/configuration.html#confval-html_theme
html_theme = globals().get('html_theme', 'alabaster')

#Add project information to the template context.
context = {
    'html_theme': html_theme,
    'current_version': "v3.5.0",
    'version_slug': "v3.5.0",
    'MEDIA_URL': "https://media.readthedocs.com/media/",
    'STATIC_URL': "https://assets.readthedocs.com/",
    'PRODUCTION_DOMAIN': "readthedocs.com",
    'proxied_static_path': "/_/static/",
    'versions': [
    ("v3.5.0", "/en/v3.5.0/"),
    ("v3.4.0", "/en/v3.4.0/"),
    ("v3.3.2", "/en/v3.3.2/"),
    ("v3.3.1", "/en/v3.3.1/"),
    ("v3.3.0", "/en/v3.3.0/"),
    ("v3.2.2", "/en/v3.2.2/"),
    ("v3.2.1", "/en/v3.2.1/"),
    ("v3.2.0", "/en/v3.2.0/"),
    ("v3.2.0b1", "/en/v3.2.0b1/"),
    ("v3.2.0b0", "/en/v3.2.0b0/"),
    ("v3.1.1", "/en/v3.1.1/"),
    ("v3.1.0", "/en/v3.1.0/"),
    ("v3.0.3", "/en/v3.0.3/"),
    ("v3.0.2", "/en/v3.0.2/"),
    ("v3.0.1", "/en/v3.0.1/"),
    ("v2.28.3", "/en/v2.28.3/"),
    ("v2.28.1", "/en/v2.28.1/"),
    ("v2.28.0", "/en/v2.28.0/"),
    ("v2.27.3", "/en/v2.27.3/"),
    ("v2.27.2", "/en/v2.27.2/"),
    ("v2.27.1", "/en/v2.27.1/"),
    ("v2.27.0", "/en/v2.27.0/"),
    ("v2.26.2", "/en/v2.26.2/"),
    ("v2.26.1", "/en/v2.26.1/"),
    ("v2.26.0", "/en/v2.26.0/"),
    ("v2.25.1", "/en/v2.25.1/"),
    ("v2.25.0", "/en/v2.25.0/"),
    ("v2.24.0", "/en/v2.24.0/"),
    ("v2.23.1", "/en/v2.23.1/"),
    ("v2.23.0", "/en/v2.23.0/"),
    ("v2.22.2", "/en/v2.22.2/"),
    ("v2.22.1", "/en/v2.22.1/"),
    ("v2.22.0", "/en/v2.22.0/"),
    ("v2.21.6", "/en/v2.21.6/"),
    ("v2.21.5", "/en/v2.21.5/"),
    ("v2.21.4", "/en/v2.21.4/"),
    ("v2.21.3", "/en/v2.21.3/"),
    ("v2.21.2", "/en/v2.21.2/"),
    ("v2.20.0", "/en/v2.20.0/"),
    ("v2.19.0", "/en/v2.19.0/"),
    ("v2.18.0", "/en/v2.18.0/"),
    ("v2.17.0", "/en/v2.17.0/"),
    ("v2.16.0", "/en/v2.16.0/"),
    ("v2.15.1", "/en/v2.15.1/"),
    ("v2.14.2", "/en/v2.14.2/"),
    ("v2.13.3", "/en/v2.13.3/"),
    ("v2.12.2", "/en/v2.12.2/"),
    ("v2.11.2", "/en/v2.11.2/"),
    ("v2.9.3", "/en/v2.9.3/"),
    ("v2.8.3", "/en/v2.8.3/"),
    ("v2.7.3", "/en/v2.7.3/"),
    ("latest-release", "/en/latest-release/"),
    ("early-access", "/en/early-access/"),
    ],
    'downloads': [ 
    ],
    'subprojects': [ 
    ],
    'slug': 'datarobot-public-api-client',
    'name': u'public_api_client',
    'rtd_language': u'en',
    'programming_language': u'py',
    'canonical_url': '',
    'analytics_code': 'None',
    'single_version': False,
    'conf_py_path': '/sdk_docs/',
    'api_host': 'https://readthedocs.com',
    'github_user': 'datarobot',
    'proxied_api_host': '/_',
    'github_repo': 'public_api_client',
    'github_version': 'v3.5.0',
    'display_github': True,
    'bitbucket_user': 'None',
    'bitbucket_repo': 'None',
    'bitbucket_version': 'v3.5.0',
    'display_bitbucket': False,
    'gitlab_user': 'None',
    'gitlab_repo': 'None',
    'gitlab_version': 'v3.5.0',
    'display_gitlab': False,
    'READTHEDOCS': True,
    'using_theme': (html_theme == "default"),
    'new_theme': (html_theme == "sphinx_rtd_theme"),
    'source_suffix': SUFFIX,
    'ad_free': False,
    'docsearch_disabled': False,
    'user_analytics_code': '',
    'global_analytics_code': 'UA-17997319-2',
    'commit': 'f12ef43d',
}

# For sphinx >=1.8 we can use html_baseurl to set the canonical URL.
# https://www.sphinx-doc.org/en/master/usage/configuration.html#confval-html_baseurl
if version_info >= (1, 8):
    if not globals().get('html_baseurl'):
        html_baseurl = context['canonical_url']
    context['canonical_url'] = None





if 'html_context' in globals():
    for key in context:
        if key not in html_context:
            html_context[key] = context[key]
else:
    html_context = context

# Add custom RTD extension
if 'extensions' in globals():
    # Insert at the beginning because it can interfere
    # with other extensions.
    # See https://github.com/rtfd/readthedocs.org/pull/4054
    extensions.insert(0, "readthedocs_ext.readthedocs")
else:
    extensions = ["readthedocs_ext.readthedocs"]

# Add External version warning banner to the external version documentation
if 'tag' == 'external':
    extensions.insert(1, "readthedocs_ext.external_version_warning")
    readthedocs_vcs_url = 'None'
    readthedocs_build_url = 'https://readthedocs.com/projects/datarobot-public-api-client/builds/2353615/'

project_language = 'en'

# User's Sphinx configurations
language_user = globals().get('language', None)
latex_engine_user = globals().get('latex_engine', None)
latex_elements_user = globals().get('latex_elements', None)

# Remove this once xindy gets installed in Docker image and XINDYOPS
# env variable is supported
# https://github.com/rtfd/readthedocs-docker-images/pull/98
latex_use_xindy = False

chinese = any([
    language_user in ('zh_CN', 'zh_TW'),
    project_language in ('zh_CN', 'zh_TW'),
])

japanese = any([
    language_user == 'ja',
    project_language == 'ja',
])

if chinese:
    latex_engine = latex_engine_user or 'xelatex'

    latex_elements_rtd = {
        'preamble': '\\usepackage[UTF8]{ctex}\n',
    }
    latex_elements = latex_elements_user or latex_elements_rtd
elif japanese:
    latex_engine = latex_engine_user or 'platex'

# Make sure our build directory is always excluded
exclude_patterns = globals().get('exclude_patterns', [])
exclude_patterns.extend(['_build'])

[rtd-command-info] start-time: 2024-07-16T23:30:51.836105Z, end-time: 2024-07-16T23:32:12.489546Z, duration: 80, exit-code: 0
python -m sphinx -T -b html -d _build/doctrees -D language=en . $READTHEDOCS_OUTPUT/html
Running Sphinx v5.3.0
Initializing Spelling Checker 8.0.0
making output directory... done
[autosummary] generating autosummary for: CHANGES.rst, autodoc/api_reference.rst, examples/index.rst, getting_started.rst, index.rst, reference/admin/credentials.rst, reference/admin/index.rst, reference/admin/sharing.rst, reference/data/database_connectivity.rst, reference/data/dataset.rst, ..., reference/modeling/spec/segmented_modeling.rst, reference/modeling/spec/time_series.rst, reference/modeling/spec/unsupervised_anomaly.rst, reference/modeling/spec/unsupervised_clustering.rst, reference/modeling/spec/visualai.rst, reference/predictions/batch_predictions.rst, reference/predictions/index.rst, reference/predictions/predict_job.rst, reference/use_cases/index.rst, reference/use_cases/use_cases.rst
building [mo]: targets for 0 po files that are out of date
building [html]: targets for 50 source files that are out of date
updating environment: [new config] 50 added, 0 changed, 0 removed
reading sources... [  2%] CHANGES
reading sources... [  4%] autodoc/api_reference
You have imported from the _experimental directory.
This directory is used for unreleased datarobot features.
Unless you specifically know better, you don't have the access to use this functionality in the app, so this code will not work.
reading sources... [  6%] examples/index
reading sources... [  8%] getting_started
reading sources... [ 10%] index
reading sources... [ 12%] reference/admin/credentials
reading sources... [ 14%] reference/admin/index
reading sources... [ 16%] reference/admin/sharing
reading sources... [ 18%] reference/data/database_connectivity
reading sources... [ 20%] reference/data/dataset
reading sources... [ 22%] reference/data/feature_discovery
reading sources... [ 24%] reference/data/index
reading sources... [ 26%] reference/index
reading sources... [ 28%] reference/mlops/custom_metrics
reading sources... [ 30%] reference/mlops/custom_model
reading sources... [ 32%] reference/mlops/data_exports
reading sources... [ 34%] reference/mlops/deployment
reading sources... [ 36%] reference/mlops/hosted_custom_metrics
reading sources... [ 38%] reference/mlops/index
reading sources... [ 40%] reference/mlops/jobs
reading sources... [ 42%] reference/mlops/key_values
reading sources... [ 44%] reference/mlops/model_registry
reading sources... [ 46%] reference/modeling/blueprint
reading sources... [ 48%] reference/modeling/index
reading sources... [ 50%] reference/modeling/insights/automated_documentation
reading sources... [ 52%] reference/modeling/insights/external_testset
reading sources... [ 54%] reference/modeling/insights/index
reading sources... [ 56%] reference/modeling/insights/prediction_explanations
reading sources... [ 58%] reference/modeling/insights/rating_table
reading sources... [ 60%] reference/modeling/insights/shap_insights
reading sources... [ 62%] reference/modeling/job
reading sources... [ 64%] reference/modeling/model
reading sources... [ 66%] reference/modeling/model_recommendation
reading sources... [ 68%] reference/modeling/prime
reading sources... [ 70%] reference/modeling/project
reading sources... [ 72%] reference/modeling/spec/binary_data
reading sources... [ 74%] reference/modeling/spec/custom_task
reading sources... [ 76%] reference/modeling/spec/datetime_partition
reading sources... [ 78%] reference/modeling/spec/index
reading sources... [ 80%] reference/modeling/spec/monotonic_constraints
reading sources... [ 82%] reference/modeling/spec/segmented_modeling
reading sources... [ 84%] reference/modeling/spec/time_series
reading sources... [ 86%] reference/modeling/spec/unsupervised_anomaly
reading sources... [ 88%] reference/modeling/spec/unsupervised_clustering
reading sources... [ 90%] reference/modeling/spec/visualai
reading sources... [ 92%] reference/predictions/batch_predictions
reading sources... [ 94%] reference/predictions/index
reading sources... [ 96%] reference/predictions/predict_job
reading sources... [ 98%] reference/use_cases/index
reading sources... [100%] reference/use_cases/use_cases

/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages/numpydoc/docscrape.py:449: UserWarning: Unknown section Attributes: in the docstring of CostMetricConfiguration in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0/datarobot/_experimental/models/genai/cost_metric_configurations.py.
  warn(msg)
/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages/numpydoc/docscrape.py:449: UserWarning: Unknown section Attributes: in the docstring of SyntheticEvaluationDataset in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0/datarobot/_experimental/models/genai/synthetic_evaluation_dataset_generation.py.
  warn(msg)
/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages/numpydoc/docscrape.py:449: UserWarning: Unknown section Parameters: in the docstring of create in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0/datarobot/_experimental/models/genai/synthetic_evaluation_dataset_generation.py.
  warn(msg)
/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages/numpydoc/docscrape.py:449: UserWarning: Unknown section Returns: in the docstring of create in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0/datarobot/_experimental/models/genai/synthetic_evaluation_dataset_generation.py.
  warn(msg)
/home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/envs/v3.5.0/lib/python3.8/site-packages/numpydoc/docscrape.py:449: UserWarning: Unknown section Attributes: in the docstring of SidecarModelMetricValidation in /home/docs/checkouts/readthedocs.org/user_builds/datarobot-public-api-client/checkouts/v3.5.0/datarobot/_experimental/models/genai/sidecar_model_metric.py.
  warn(msg)
WARNING: error while formatting arguments for datarobot.models.anomaly_assessment.AnomalyAssessmentRecord: __name__
WARNING: error while formatting arguments for datarobot.models.anomaly_assessment.AnomalyAssessmentExplanations: __name__
WARNING: error while formatting arguments for datarobot.models.anomaly_assessment.AnomalyAssessmentPredictionsPreview: __name__
looking for now-outdated files... none found
pickling environment... done
checking consistency... done
preparing documents... done
writing output... [  2%] CHANGES
writing output... [  4%] autodoc/api_reference
writing output... [  6%] examples/index
writing output... [  8%] getting_started
writing output... [ 10%] index
writing output... [ 12%] reference/admin/credentials
writing output... [ 14%] reference/admin/index
writing output... [ 16%] reference/admin/sharing
writing output... [ 18%] reference/data/database_connectivity
writing output... [ 20%] reference/data/dataset
writing output... [ 22%] reference/data/feature_discovery
writing output... [ 24%] reference/data/index
writing output... [ 26%] reference/index
writing output... [ 28%] reference/mlops/custom_metrics
writing output... [ 30%] reference/mlops/custom_model
writing output... [ 32%] reference/mlops/data_exports
writing output... [ 34%] reference/mlops/deployment
writing output... [ 36%] reference/mlops/hosted_custom_metrics
writing output... [ 38%] reference/mlops/index
writing output... [ 40%] reference/mlops/jobs
writing output... [ 42%] reference/mlops/key_values
writing output... [ 44%] reference/mlops/model_registry
writing output... [ 46%] reference/modeling/blueprint
writing output... [ 48%] reference/modeling/index
writing output... [ 50%] reference/modeling/insights/automated_documentation
writing output... [ 52%] reference/modeling/insights/external_testset
writing output... [ 54%] reference/modeling/insights/index
writing output... [ 56%] reference/modeling/insights/prediction_explanations
writing output... [ 58%] reference/modeling/insights/rating_table
writing output... [ 60%] reference/modeling/insights/shap_insights
writing output... [ 62%] reference/modeling/job
writing output... [ 64%] reference/modeling/model
writing output... [ 66%] reference/modeling/model_recommendation
writing output... [ 68%] reference/modeling/prime
writing output... [ 70%] reference/modeling/project
writing output... [ 72%] reference/modeling/spec/binary_data
writing output... [ 74%] reference/modeling/spec/custom_task
writing output... [ 76%] reference/modeling/spec/datetime_partition
writing output... [ 78%] reference/modeling/spec/index
writing output... [ 80%] reference/modeling/spec/monotonic_constraints
writing output... [ 82%] reference/modeling/spec/segmented_modeling
writing output... [ 84%] reference/modeling/spec/time_series
writing output... [ 86%] reference/modeling/spec/unsupervised_anomaly
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[1] [2] [1] [2]
Chapter 1.
[3] [4]
Chapter 2.
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[][][]\T1/txtt/m/sl/10 Dataset.create_from_url[][] \T1/qtm/m/n/10 takes .csv da
ta from a URL. If you have set

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[][][]\T1/txtt/m/sl/10 Dataset.create_from_data_source[][] \T1/qtm/m/n/10 takes
 data from a data source. If you have set
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[]\T1/qtm/m/n/10 For mul-ti-class mod-els, you can get a list of per-class lift
 charts us-ing the \T1/txtt/m/n/10 Model \T1/qtm/m/n/10 method

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[]\T1/qtm/m/n/10 Just as with the lift and ROC charts, you can use \T1/txtt/m/n
/10 Model \T1/qtm/m/n/10 meth-ods \T1/txtt/m/n/10 get_residuals_chart \T1/qtm/m
/n/10 and
[37] [38] [39] [40] [41] [42] [43] [44]
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[]\T1/qtm/m/n/10 gap_duration (str): A du-ra-tion string such as those re-turne
d by the [][]\T1/txtt/m/sl/10 partitioning_methods.
[45]
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\T1/qtm/m/n/10 and \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 . Us-ing
 the same date for both \T1/txtt/m/n/10 primary_training_end_date \T1/qtm/m/n/1
0 and
[46]
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[]\T1/qtm/m/n/10 For date-time par-ti-tioned model you can re-trieve the Ac-cu-
racy over Time plot. To do so use

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[][]\T1/txtt/m/sl/10 DatetimeModel.get_accuracy_over_time_plot[][]\T1/qtm/m/n/1
0 . You can also re-trieve the de-tailed meta-data us-ing
[47] [48] [49] [50] [51]
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[]\T1/qtm/m/n/10 Enough rows of his-tor-i-cal data must be pro-vided to cover t
he span of the ef-fec-tive Fea-ture Deriva-
[52] [53] [54] [55]
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[]\T1/qtm/m/n/10 Pre-dic-tion in-ter-vals can be cal-cu-lated for a [][]\T1/txt
t/m/sl/10 DatetimeModel[][] \T1/qtm/m/n/10 us-ing the [][]\T1/txtt/m/sl/10 Date
timeModel.
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[]\T1/qtm/m/n/10 1. Up-load a pre-dic-tion dataset, spec-i-fy-ing \T1/txtt/m/n/
10 predictions_start_date\T1/qtm/m/n/10 , \T1/txtt/m/n/10 predictions_end_date\
T1/qtm/m/n/10 , and
[71]
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[]\T1/qtm/m/n/10 Up-load a pre-dic-tion dataset that con-tains la-bel col-umn(s
), re-quest com-pute ex-ter-nal test on one of
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\T1/qtm/b/n/10 Note:  \T1/txtt/m/n/10 PredictionExplanations.get_all_as_datafra
me() \T1/qtm/m/n/10 and \T1/txtt/m/n/10 PredictionExplanations.
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[]\T1/qtm/m/n/10 If you just want to get gen-er-ated pre-dic-tions from a Pre-d
ic-tJob, you can use the \T1/txtt/m/n/10 PredictJob.
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[]\T1/qtm/m/n/10 In or-der to sched-ule the ex-e-cu-tion of a Batch Pre-dic-tio
n job, a def-i-ni-tion must first be cre-ated, us-
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[]|\T1/qtm/m/n/10 The hour(s)

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[]\T1/qtm/m/n/10 Job def-i-ni-tions are only be ex-e-cuted by the sched-uler if
 \T1/txtt/m/n/10 enabled \T1/qtm/m/n/10 is set to \T1/txtt/m/n/10 True\T1/qtm/m
/n/10 . If you have a

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[]\T1/qtm/m/n/10 When cre-at-ing a new de-ploy-ment, a DataRobot \T1/txtt/m/n/1
0 registered_model_version_id\TS1/txtt/m/n/10 ``\T1/txtt/m/n/10 (also known as
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\T1/qtm/m/n/10 of [][]\T1/txtt/m/sl/10 datarobot.models.deployment.DeploymentGr
antSharedRoleWithId[][] \T1/qtm/m/n/10 and [][]\T1/txtt/m/sl/10 datarobot.model
s.
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[]\T1/qtm/m/n/10 Re-fer to [][]\T1/txtt/m/sl/10 ExecutionEnvironment[][] \T1/qt
m/m/n/10 for prop-er-ties of the ex-e-cu-tion en-vi-ron-ment ob-ject and
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[]\T1/qtm/m/n/10 cus-tom_model.update(is_training_data_for_versions_permanently
_enabled=True) cus-
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[]\T1/qtm/m/n/10 To cre-ate a hosted cus-tom met-ric job from gallery tem-plate
, use \T1/qtm/m/it/10 dr.registry.Job.create_from_custom_metric_gallery_templat
e\T1/qtm/m/n/10 ,
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[]\T1/qtm/m/n/10 You can also fil-ter the reg-is-tered model ver-sions that are
 re-turned by pass-ing an in-stance of the
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[]\T1/qtm/m/n/10 Use Cases sup-port \T1/txtt/m/n/10 SHARING_ROLE.OWNER\T1/qtm/m
/n/10 , \T1/txtt/m/n/10 SHARING_ROLE.EDITOR\T1/qtm/m/n/10 , \T1/txtt/m/n/10 SHA
RING_ROLE.CONSUMER \T1/qtm/m/n/10 and
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\T1/qtm/m/n/10 (New in ver-sion v2.23) one of \T1/txtt/m/n/10 datarobot.enums.

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\T1/qtm/m/n/10 ness. Can be one of \T1/txtt/m/n/10 proportionalParity\T1/qtm/m/
n/10 , \T1/txtt/m/n/10 equalParity\T1/qtm/m/n/10 ,

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\T1/txtt/m/n/10 predictionBalance\T1/qtm/m/n/10 , \T1/txtt/m/n/10 trueFavorable
AndUnfavorableRateParity \T1/qtm/m/n/10 or
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\T1/qtm/m/it/10 **record_kwargs\T1/txtt/m/n/10 )|  
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\T1/qtm/m/n/10 [string] The URL for the pre-dic-tion dataset (e.g.:

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\T1/qtm/m/n/10 [string] The URL for the scored dataset (e.g.: \T1/qtm/m/it/10 h
ttps://storage_account.blob.endpoint/container/blob_name\T1/qtm/m/n/10 ) 
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\T1/qtm/m/n/10 [string] The URL for the pre-dic-tion dataset (e.g.:

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\T1/qtm/m/n/10 [string] The URL for the scored dataset (e.g.: \T1/qtm/m/it/10 h
ttp(s)://storage.googleapis.com/[bucket]/[object]\T1/qtm/m/n/10 ) 
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[]\T1/qtm/m/n/10 par-ti-tion : sub-set of train-ing data to score, one of \T1/t
xtt/m/n/10 datarobot.enums.
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\T1/qtm/m/it/10 tered_model_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 tered_model_version\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 dated_at=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 dated_by=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 mlpkg_file_contents=None\T1/txtt/m/n/10 )|  
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\T1/qtm/m/it/10 ment_attribute=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 ment_value=None\T1/txtt/m/n/10 )|  
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\T1/qtm/m/it/10 ment_attribute=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 ment_value=None\T1/txtt/m/n/10 )|  
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\T1/qtm/m/it/10 tom_metric_metadata\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 plate_metric_type\T1/txtt/m/n/10 )|  
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\T1/qtm/m/n/10 Cre-ate a hosted cus-tom met-ric from a tem-plate. A short-cut f
or 2 calls:
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\T1/qtm/m/it/10 is_model_specific\T1/qtm/m/n/10 , 
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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.REGRESSION\T1/qtm/m/n/10 , \T1/qtm/m/it/1
0 datarobot.TARGET_TYPE.MULTICLASS\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED\T1/qtm/m/n/10 , \T1/qtm/m/it
/10 datarobot.TARGET_TYPE.ANOMALY\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED \T1/qtm/m/n/10 or \T1/qtm/m/
it/10 datarobot.TARGET_TYPE.ANOMALY
[333]
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.REGRESSION\T1/qtm/m/n/10 , \T1/qtm/m/it/1
0 datarobot.TARGET_TYPE.MULTICLASS\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED\T1/qtm/m/n/10 , \T1/qtm/m/it
/10 datarobot.TARGET_TYPE.TEXT_GENERATION\T1/qtm/m/n/10 ] 

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n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 the type of the im-age, ei-ther CUS-TOM_MODEL_IMAGE_TYPE.CUSTOM_
MODEL_IMAGE

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\T1/qtm/m/n/10 if the test-ing at-tempt is us-ing a Cus-tom-Mod-e-lIm-age as it
s model or CUS-
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,

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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 The base en-vi-ron-ment to use with this model ver-sion. At leas
t one of

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\T1/qtm/m/n/10 ^^Pfile1.txt^^Q), (^^P/home/user/Documents/myModel/folder/file2.
txt^^Q,

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n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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t one of

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\T1/qtm/m/n/10 ^^Pfile1.txt^^Q), (^^P/home/user/Documents/myModel/folder/file2.
txt^^Q,

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\T1/qtm/m/n/10 ^^Pfolder/file2.txt^^Q)] or [^^P/home/user/Documents/myModel/fil
e1.txt^^Q,

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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
[347]
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\T1/qtm/m/n/10 build sta-tus of the ex-e-cu-tion en-vi-ron-ment ver-sion to fil
-ter by. See

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\T1/qtm/m/n/10 datarobot.enums.EXECUTION_ENVIRONMENT_VERSION_BUILD_STATUS
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\T1/qtm/m/n/10 whether anomaly pre-dic-tions should be cal-i-brated to be be-tw
een 0

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\T1/qtm/m/n/10 and 1 by DR. only ap-plies to cus-tom es-ti-ma-tors with tar-get
 type
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[376] [377] [378] [379] [380] [381]
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\T1/qtm/m/n/10 [str] Op-tional. The full JDBC URL (for ex-am-ple:

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\T1/qtm/m/n/10 [str] Op-tional. The iden-ti-fier of the Con-nec-tor. if the typ
e is Data-S-tore-

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\T1/qtm/m/n/10 [str] Op-tional. The full JDBC URL (for ex-am-ple:
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\T1/qtm/m/n/10 SCHEMA . TABLE _ NAME$[][]' - `[][]$jdbc : DATA _ SOURCE _ GIVEN
 _ NAME$[][]/<query>' - for
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\T1/qtm/m/it/10 only_matched_predictions=None\T1/qtm/m/n/10 , 
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 [list] To cre-ate or up-date ex-ist-ing seg-ment anal-y-sis at-t
ributes, see
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\T1/qtm/m/n/10 [bool] If pre-dic-tions data col-lec-tion is en-abled for this d
e-ploy-

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\T1/qtm/m/n/10 ment. To up-date ex-ist-ing `'pre-dic-tions_data_collection'' se
t-tings, see
[449]
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\T1/qtm/m/n/10 [bool] If tar-get pre-dic-tion_warning is en-abled for this de-p
loy-ment.

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\T1/qtm/m/n/10 To cre-ate or up-date ex-ist-ing `'pre-dic-tion_warning'' set-ti
ngs, see
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\T1/qtm/m/it/10 tected_feature=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 ness_threshold=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 model_package_id=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 able_target_outcome=None\T1/txtt/m/n/10 )|  
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[]\T1/qtm/m/it/10 baseline_validation_job_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 project_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 log_version_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 time_partition_column\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 is_external_baseline_dataset_valid\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 series_id_columns=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 out_start_date=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 out_end_date=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 tests=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 cast_window_start=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 cast_window_end=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 sage=None\T1/txtt/m/n/10 )|  
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[]\T1/qtm/m/n/10 {`key':'DataRobot', `sum-mary':{`min':0, `max':29815.0, `std-D
ev':6498.029,
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[]\T1/qtm/m/n/10 {`key':'DataRobot', `sum-mary':{`min':0, `max':29815.0, `std-D
ev':6498.029,
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Underfull \hbox (badness 10000) in paragraph at lines 42429--42432
[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0,B=1) can be re-trieved via:

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\T1/txtt/m/n/10 pairwise_joint_probabilities.statistic_dataframes[(0,1)].loc[\T
S1/txtt/m/n/10 '\T1/txtt/m/n/10 A\TS1/txtt/m/n/10 '\T1/txtt/m/n/10 ,

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[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0,B=1) can be re-trieved via:
[502]
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\T1/qtm/m/n/10 [list(dict)] List of con-di-tional prob-a-bil-ity val-ues with a
 schema de-scribed as

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[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0|B=1) can be re-trieved via:

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\T1/txtt/m/n/10 pairwise_conditional_probabilities.statistic_dataframes[(0,1)].

[503] [504]
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\T1/qtm/m/n/10 [enums.FEATURE_ASSOCIATION_METRIC] The name of a met-ric to

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\T1/qtm/m/n/10 get pair-wise data for. Since `v2.19' this is op-tional and de-f
aults to

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\T1/qtm/m/n/10 [enums.FEATURE_ASSOCIATION_TYPE] The type of de-pen-

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\T1/qtm/m/n/10 dence for the data. Since `v2.19' this is op-tional and de-fault
s to
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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
[514]
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\T1/qtm/m/n/10 Time unit of the pre-dic-tion point round-ing. One of \T1/txtt/m
/n/10 datarobot.enums.

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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
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[]\T1/qtm/m/it/10 ff_metadata_datetime_per_backtest\T1/txtt/m/n/10 )|  
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 48881--48886
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[564] [565] [566] [567] [568] [569]
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.
[570]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 49537--49542
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 55200--55205
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[624] [625] [626] [627] [628] [629]
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.

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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 55856--55861
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[630] [631] [632] [633] [634]
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\T1/qtm/m/n/10 of the \T1/txtt/m/n/10 windows_basis_unit \T1/qtm/m/n/10 into th
e past rel-a-tive to the fore-cast point the

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\T1/txtt/m/n/10 feature_derivation_window_start \T1/qtm/m/n/10 set on the proje
ct due to the dif-fer-enc-ing
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 56601--56606
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[639] [640] [641] [642] [643] [644] [645] [646] [647] [648] [649]
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\T1/qtm/m/n/10 [AnomalyOverTimePlotPreview] a [][]\T1/txtt/m/sl/10 AnomalyOverT
imePlotPreview[][] \T1/qtm/m/n/10 rep-re-sent-ing
[650]
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\T1/qtm/m/n/10 [list of Anoma-lyAssess-men-tRecord] a [][]\T1/txtt/m/sl/10 Anom
alyAssessmentRecord[][] \T1/qtm/m/n/10 rep-re-sent-ing
[651]
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Lift chart data source. Ch
eck

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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Lift chart data source. Ch
eck
[654]
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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Roc Curve data source. Che
ck

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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) ROC curve data source. Che
ck
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[667] [668] [669]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 59878--59883
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[670] [671] [672] [673]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 60185--60190
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[674] [675] [676] [677] [678] [679] [680] [681] [682] [683] [684] [685]
[686] [687] [688] [689]
Underfull \hbox (badness 5359) in paragraph at lines 61731--61734
\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 63071--63076
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[701] [702] [703] [704] [705] [706] [707]
Underfull \hbox (badness 5592) in paragraph at lines 63679--63685
\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

Underfull \hbox (badness 10000) in paragraph at lines 63679--63685
\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.

Underfull \hbox (badness 10000) in paragraph at lines 63727--63732
[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 63727--63732
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[708] [709] [710] [711] [712] [713] [714] [715] [716] [717] [718]
Overfull \hbox (3.26418pt too wide) in paragraph at lines 64948--64948
\T1/qtm/m/it/10 low_partial_history_time_series_predictions=False\T1/qtm/m/n/10
 , 

Underfull \hbox (badness 10000) in paragraph at lines 64958--64961
[]\T1/qtm/m/n/10 This is the spec-i-fi-ca-tion that should be passed to [][]\T1
/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the
[719]
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[]\T1/qtm/m/n/10 Note that ei-ther (\T1/txtt/m/n/10 holdout_start_date\T1/qtm/m
/n/10 , \T1/txtt/m/n/10 holdout_duration\T1/qtm/m/n/10 ) or (\T1/txtt/m/n/10 ho
ldout_start_date\T1/qtm/m/n/10 ,

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\T1/qtm/m/n/10 [str] one of \T1/txtt/m/n/10 datarobot.enums.DATETIME_AUTOPILOT_
DATA_SELECTION_METHOD\T1/qtm/m/n/10 .

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\T1/qtm/m/n/10 [datetime.datetime or None] The start date of hold-out scor-ing 
data. If
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[]\T1/qtm/m/n/10 Op-tion 2 (New in ver-sion v2.20): Use \T1/txtt/m/n/10 index\T
1/qtm/m/n/10 , \T1/txtt/m/n/10 primary_training_start_date\T1/qtm/m/n/10 ,
[723] [724] [725]
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\T1/qtm/m/n/10 [str] one of \T1/txtt/m/n/10 datarobot.enums.DATETIME_AUTOPILOT_
DATA_SELECTION_METHOD\T1/qtm/m/n/10 .
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\T1/qtm/m/n/10 proach for spec-i-fy-ing back-tests (\T1/txtt/m/n/10 gap_duratio
n\T1/qtm/m/n/10 , \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 , and
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[]\T1/qtm/m/n/10 This is the spec-i-fi-ca-tion that should be passed to [][]\T1
/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the

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\T1/txtt/m/n/10 partitioning_method \T1/qtm/m/n/10 pa-ram-e-ter. To see the ful
l par-ti-tion-ing use [][]\T1/txtt/m/sl/10 DatetimePartitioning.
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\T1/qtm/m/n/10 [bool] De-fault \T1/txtt/m/n/10 False\T1/qtm/m/n/10 . If \T1/txt
t/m/n/10 False\T1/qtm/m/n/10 , will use a duration-based ap-proach

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\T1/qtm/m/n/10 for spec-i-fy-ing back-tests (\T1/txtt/m/n/10 gap_duration\T1/qt
m/m/n/10 , \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 , and

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\T1/qtm/m/n/10 ing back-tests (\T1/txtt/m/n/10 primary_training_start_date\T1/q
tm/m/n/10 , \T1/txtt/m/n/10 primary_training_end_date\T1/qtm/m/n/10 ,
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[748]
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[]\T1/qtm/m/n/10 Com-pute a Pre-dic-tion-Ex-pla-na-tion-sIni-tial-iza-tion for 
the model via \T1/txtt/m/n/10 datarobot.

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[]\T1/qtm/m/n/10 Com-pute pre-dic-tions for the model and dataset via \T1/txtt/
m/n/10 datarobot.Model.
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\T1/qtm/m/n/10 Cre-ate pre-dic-tion ex-pla-na-tions for the the dataset used to
 train the model. This can be

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\T1/qtm/m/n/10 re-trieved by call-ing \T1/txtt/m/n/10 dr.Model.get().featurelis
t_id\T1/qtm/m/n/10 . For OTV and time-series projects,

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[]\T1/qtm/m/n/10 Com-pute a Pre-dic-tion-Ex-pla-na-tion-sIni-tial-iza-tion for 
the model via \T1/txtt/m/n/10 datarobot.

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[]\T1/qtm/m/n/10 Com-pute pre-dic-tions for the model and dataset via \T1/txtt/
m/n/10 datarobot.Model.
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\T1/qtm/m/it/10 tion_explanations=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 justed_prediction=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 justed_prediction_values=None\T1/txtt/m/n/10 )|  

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[]\T1/qtm/m/n/10 Project.list(search_params={`project_name': `red'}) >>> [Proje
ct(`Prediction Time'),
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\T1/qtm/m/n/10 [ClassMappingAggregationSettings, op-tional] In-stance of \T1/tx
tt/m/n/10 datarobot.helpers.
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\T1/qtm/m/n/10 level: \T1/qtm/m/it/10 mono-tonic_increasing_featurelist_id\T1/q
tm/m/n/10 , \T1/qtm/m/it/10 mono-tonic_decreasing_featurelist_id\T1/qtm/m/n/10 
,

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\T1/qtm/m/it/10 sup-ports_composable_ml \T1/qtm/m/n/10 and \T1/qtm/m/it/10 sup-
ports_monotonic_constraints\T1/qtm/m/n/10 . Fol-low-ing at-

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\T1/qtm/m/n/10 tributes are ab-sent and could be re-trieved from the in-di-vid-
ual model level:

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\T1/qtm/m/it/10 has_empty_clusters\T1/qtm/m/n/10 , \T1/qtm/m/it/10 is_n_cluster
s_dynamically_determined\T1/qtm/m/n/10 , \T1/qtm/m/it/10 pre-dic-tion_threshold

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\T1/qtm/m/n/10 Raised if \T1/txtt/m/n/10 forecast_point \T1/qtm/m/n/10 or \T1/t
xtt/m/n/10 predictions_start_date \T1/qtm/m/n/10 and
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

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[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
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\T1/qtm/m/n/10 (New in ver-sion v2.23) one of \T1/txtt/m/n/10 datarobot.enums.

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\T1/txtt/m/n/10 DATETIME_AUTOPILOT_DATA_SAMPLING_METHOD\T1/qtm/m/n/10 . Ap-pli-
ca-ble for OTV projects
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\T1/qtm/m/n/10 (New in ver-sion v2.24) Met-ric to use for cal-cu-lat-ing fair-

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\T1/qtm/m/n/10 ness. Can be one of \T1/txtt/m/n/10 proportionalParity\T1/qtm/m/
n/10 , \T1/txtt/m/n/10 equalParity\T1/qtm/m/n/10 ,

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\T1/txtt/m/n/10 predictionBalance\T1/qtm/m/n/10 , \T1/txtt/m/n/10 trueFavorable
AndUnfavorableRateParity \T1/qtm/m/n/10 or
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\T1/qtm/m/n/10 [PartitioningMethod, op-tional] An in-stance of \T1/txtt/m/n/10 
datarobot.helpers.
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\T1/qtm/m/n/10 If value of \T1/txtt/m/n/10 variable_type \T1/qtm/m/n/10 is not 
from \T1/txtt/m/n/10 datarobot.enums.
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\T1/qtm/m/n/10 In-stance of the Date-timePar-ti-tion-ing de-fined in \T1/txtt/m
/n/10 datarobot.helpers.
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[]\T1/qtm/m/n/10 This is an al-ter-na-tive to pass-ing a spec-i-fi-ca-tion to [
][]\T1/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the
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\T1/qtm/m/n/10 [Optional[RegisteredModelVersionsListFilters]] A Reg-is-tered-Mo
d-elVer-sion-sList-Fil-ters
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[]\T1/qtm/m/n/10 Added a new class :class: \T1/qtm/m/it/10 Eval-u-a-tion-Datase
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[]\T1/qtm/m/n/10 Added a new class :class: \T1/qtm/m/it/10 Eval-u-a-tion-Datase
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[]\T1/qtm/m/n/10 Added a new class :class: \T1/qtm/m/it/10 Syn-thet-icE-val-u-a
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[921]
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\T1/txtt/m/sl/10 run[][] [][]BatchMonitoringJob.get_status[][] [][]BatchMonitor
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[]\T1/qtm/m/n/10 Added [][]\T1/txtt/m/sl/10 DatetimePartitioningId[][]\T1/qtm/m
/n/10 , which can be passed as a \T1/qtm/m/it/10 par-ti-tion-ing_method \T1/qtm
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\T1/txtt/m/sl/10 create_from_url[][] [][]Dataset.create_from_data_source[][] []
[]Dataset.create_from_query_generator[][]

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[][]\T1/txtt/m/sl/10 Dataset.create_project[][] [][]Project.create[][] [][]Proj
ect.create_from_data_source[][] [][]Project.

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[]\T1/qtm/m/n/10 If the user con-fig-ures the client via env vars, then set the
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[]\T1/qtm/m/n/10 Added method meth:\T1/qtm/m/it/10 Deployment.get_predictions_o
ver_time <datarobot.models.Deployment.get_predictions_over_time>

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hart[][] [][]Model.get_roc_curve[][] [][]Model.
[923]
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[]\T1/qtm/m/n/10 Added new method for re-triev-ing all avail-able fea-ture im-p
acts for the model [][]\T1/txtt/m/sl/10 Model.

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\T1/txtt/m/sl/10 PredictionExplanations.get_all_as_dataframe()[][] \T1/qtm/m/n/
10 and [][]\T1/txtt/m/sl/10 datarobot.PredictionExplanations.
[924]
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[]\T1/qtm/m/n/10 The sliced in-sight API end-point \T1/qtm/m/it/10 GET: api/v2/
insights/<insight_name>/ \T1/qtm/m/n/10 re-turns a pag-i-nated re-

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[]\T1/txtt/m/n/10 DatetimeModel.get_feature_fit_metadata \T1/qtm/m/n/10 has bee
n re-moved. Use [][]\T1/txtt/m/sl/10 DatetimeModel.

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[]\T1/txtt/m/n/10 DatetimeModel.request_feature_fit \T1/qtm/m/n/10 has been re-
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[]\T1/txtt/m/n/10 Model.get_or_request_feature_fit \T1/qtm/m/n/10 has been re-m
oved. Use [][]\T1/txtt/m/sl/10 Model.

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[]\T1/txtt/m/n/10 DatetimeModel.get_or_request_feature_fit \T1/qtm/m/n/10 has b
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[]\T1/qtm/m/n/10 Dep-re-cated the fol-low-ing meth-ods for re-triev-ing [][]\T1
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/sl/10 DataStore.
[925]

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[926]
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[]\T1/qtm/m/n/10 Added new meth-ods [][]\T1/txtt/m/sl/10 BatchPredictionJob.app
ly_time_series_data_prep_and_score[][] \T1/qtm/m/n/10 and

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[][]\T1/txtt/m/sl/10 BatchPredictionJob.apply_time_series_data_prep_and_score_t
o_file[][] \T1/qtm/m/n/10 that ap-ply time se-ries

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or.prepare_prediction_dataset[][] \T1/qtm/m/n/10 and

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atalog[][] \T1/qtm/m/n/10 that ap-ply time se-ries

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[]\T1/qtm/m/n/10 Added two new meth-ods to the Im-ageAug-men-ta-tion-List class
: [][]\T1/txtt/m/sl/10 ImageAugmentationList.list[][]\T1/qtm/m/n/10 ,
[927] [928] [929]
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[]\T1/qtm/m/n/10 Added sup-port for cre-at-ing mono-tonic fea-ture lists for ti
me se-ries projects. Set

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[]\T1/qtm/m/n/10 Added in-for-ma-tion about ver-tex to ad-vanced tun-ing pa-ram
-e-ters [][]\T1/txtt/m/sl/10 datarobot.models.Model.
[930]
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[][][]\T1/txtt/m/sl/10 CustomModelVersion[][]\T1/qtm/m/n/10 's \T1/txtt/m/n/10 
required_metadata \T1/qtm/m/n/10 pa-ram-e-ter has been re-moved. Use

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[][][]\T1/txtt/m/sl/10 CustomTaskVersion[][]\T1/qtm/m/n/10 's \T1/txtt/m/n/10 r
equired_metadata \T1/qtm/m/n/10 pa-ram-e-ter has been re-moved. Use

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[]\T1/qtm/m/n/10 The [][]\T1/txtt/m/sl/10 Deployment[][] \T1/qtm/m/n/10 method 
\T1/txtt/m/n/10 create_from_custom_model_image \T1/qtm/m/n/10 was re-moved. Use
 [][]\T1/txtt/m/sl/10 Deployment.
[931]
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[]\T1/qtm/m/n/10 Added ex-per-i-men-tal sup-port to re-trieve doc-u-ment text e
x-trac-tion sam-ples us-

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\T1/qtm/m/n/10 ing: - [][]\T1/txtt/m/sl/10 DocumentTextExtractionSample[][] \T1
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[]\T1/qtm/m/n/10 Added sup-port to pass cal-cu-la-tion mode to pre-dic-tion ex-
pla-na-tions (\T1/qtm/m/it/10 mode \T1/qtm/m/n/10 pa-ram-e-ter in
[932]
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\T1/qtm/m/n/10 - [][]\T1/txtt/m/sl/10 Project.apply_bias_mitigation[][] \T1/qtm
/m/n/10 - [][]\T1/txtt/m/sl/10 Project.request_bias_mitigation_feature_info[][]


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\T1/qtm/m/n/10 - [][]\T1/txtt/m/sl/10 Project.get_bias_mitigation_feature_info[
][] \T1/qtm/m/n/10 and by adding new bias mit-

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\T1/qtm/m/n/10 i-ga-tion params - bias_mitigation_feature_name - bias_mitigatio
n_technique - in-

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\T1/qtm/m/n/10 clude_bias_mitigation_feature_as_predictor_variable to the ex-is
t-ing method - [][]\T1/txtt/m/sl/10 Project.start[][] \T1/qtm/m/n/10 and

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\T1/qtm/m/n/10 by adding this enum to sup-ply params to some of the above func-
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[933]
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[]\T1/qtm/m/n/10 Up-date the doc-u-men-ta-tion to sug-gest that \T1/qtm/m/it/10
 fea-ture_derivation_window_end \T1/qtm/m/n/10 of [][]\T1/txtt/m/sl/10 datarobo
t.

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[]\T1/qtm/m/n/10 Added the abil-ity to turn off su-per-vised fea-ture re-duc-ti
on for Time Se-ries projects. Op-tion
[934] [935]
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[]\T1/txtt/m/n/10 DatetimeModel.get_feature_fit <datarobot.models.DatetimeModel
.

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[]\T1/qtm/m/n/10 Dep-re-cat-ing sca-le-out pa-ram-e-ters for projects / mod-els
. In-cludes \T1/txtt/m/n/10 scaleout_modeling_mode\T1/qtm/m/n/10 ,
[936]
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[]\T1/qtm/m/n/10 Added the abil-ity to up-load a pre-dic-tion dataset into a pr
oject from the AI cat-a-log [][]\T1/txtt/m/sl/10 Project.
[937]
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[]\T1/qtm/m/n/10 Added the abil-ity to con-trol class map-ping ag-gre-ga-tion i
n mul-ti-class projects via

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[]\T1/qtm/m/n/10 Added the abil-ity to com-pute and re-trieve Fea-ture Ef-fects
 for a Mul-ti-class model us-

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\T1/qtm/m/n/10 ing [][]\T1/txtt/m/sl/10 datarobot.models.Model.request_feature_
effects_multiclass()[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 datarobot.

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\T1/txtt/m/sl/10 models.Model.get_feature_effects_multiclass()[][] \T1/qtm/m/n/
10 or [][]\T1/txtt/m/sl/10 datarobot.models.Model.

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\T1/txtt/m/sl/10 get_or_request_feature_effects_multiclass()[][] \T1/qtm/m/n/10
 meth-ods. For date-time mod-els use fol-low-

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\T1/qtm/m/n/10 ing meth-ods [][]\T1/txtt/m/sl/10 datarobot.models.DatetimeModel
.request_feature_effects_multiclass()[][]\T1/qtm/m/n/10 ,

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[][]\T1/txtt/m/sl/10 datarobot.models.DatetimeModel.get_feature_effects_multicl
ass()[][] \T1/qtm/m/n/10 or [][]\T1/txtt/m/sl/10 datarobot.models.
[938]
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[]\T1/qtm/m/n/10 fix [][]\T1/txtt/m/sl/10 datarobot.CustomTaskVersion[][] \T1/q
tm/m/n/10 and [][]\T1/txtt/m/sl/10 datarobot.CustomModelVersion[][] \T1/qtm/m/n
/10 to cor-rectly for-mat
[939]
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[]\T1/qtm/m/n/10 Added the abil-ity to re-quest a spe-cific model be pre-pared 
for de-ploy-ment us-ing [][]\T1/txtt/m/sl/10 Project.
[940] [941]
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[]\T1/qtm/m/n/10 The \T1/txtt/m/n/10 required_metadata \T1/qtm/m/n/10 prop-erty
 of [][]\T1/txtt/m/sl/10 datarobot.CustomModelVersion[][] \T1/qtm/m/n/10 has be
en dep-re-cated.

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[]\T1/qtm/m/n/10 The \T1/txtt/m/n/10 required_metadata \T1/qtm/m/n/10 prop-erty
 of [][]\T1/txtt/m/sl/10 datarobot.CustomTaskVersion[][] \T1/qtm/m/n/10 has bee
n dep-re-cated.
[942]
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[]\T1/qtm/m/n/10 Sup-port for Batch Pre-dic-tion Job Def-i-ni-tions has now bee
n added through the fol-low-ing class:

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[]\T1/qtm/m/n/10 Added method to down-load fea-ture dis-cov-ery recipe SQLs (li
m-ited beta fea-ture). [][]\T1/txtt/m/sl/10 Project.
[943]
Underfull \hbox (badness 10000) in paragraph at lines 87403--87408
[]\T1/qtm/m/n/10 Par-tial his-tory pre-dic-tions can be made with time se-ries 
time se-ries mul-ti-series mod-els us-

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\T1/qtm/m/n/10 ing the \T1/txtt/m/n/10 allow_partial_history_time_series_predic
tions \T1/qtm/m/n/10 at-tribute of the [][]\T1/txtt/m/sl/10 datarobot.

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[][]\T1/txtt/m/sl/10 PairwiseJointProbabilities[][] \T1/qtm/m/n/10 and [][]\T1/
txtt/m/sl/10 PairwiseConditionalProbabilities[][] \T1/qtm/m/n/10 or [][]\T1/txt
t/m/sl/10 Feature.

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\T1/txtt/m/sl/10 get_pairwise_correlations[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/s
l/10 Feature.get_pairwise_joint_probabilities[][] \T1/qtm/m/n/10 and [][]\T1/tx
tt/m/sl/10 Feature.
[944]
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[]\T1/qtm/m/n/10 Sup-port for down-load-ing fea-ture dis-cov-ery train-ing or p
re-dic-tion dataset us-ing [][]\T1/txtt/m/sl/10 Project.

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[]\T1/qtm/m/n/10 Added [][]\T1/txtt/m/sl/10 datarobot.models.FeatureAssociation
Matrix[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 datarobot.models.

Underfull \hbox (badness 10000) in paragraph at lines 87504--87510
\T1/txtt/m/sl/10 FeatureAssociationMatrixDetails[][] \T1/qtm/m/n/10 and [][]\T1
/txtt/m/sl/10 datarobot.models.FeatureAssociationFeaturelists[][]

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[]\T1/qtm/m/n/10 Re-move \T1/qtm/m/it/10 de-sired_memory \T1/qtm/m/n/10 param f
rom the fol-low-ing classes: [][]\T1/txtt/m/sl/10 datarobot.CustomInferenceMode
l[][]\T1/qtm/m/n/10 ,

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[]\T1/qtm/m/n/10 Re-move \T1/txtt/m/n/10 desired_memory \T1/qtm/m/n/10 param fr
om the fol-low-ing meth-ods: [][]\T1/txtt/m/sl/10 CustomInferenceModel.

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\T1/txtt/m/sl/10 create[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 CustomModelVer
sion.create_clean[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 CustomModelVersion.c
reate_from_previous[][]\T1/qtm/m/n/10 ,
[945]
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[]\T1/qtm/m/n/10 Fea-ture dis-cov-ery projects can now be cre-ated us-ing the [
][]\T1/txtt/m/sl/10 Project.start[][] \T1/qtm/m/n/10 method by pro-vid-ing
[946]
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[]\T1/qtm/m/n/10 New \T1/txtt/m/n/10 sampling_method \T1/qtm/m/n/10 param in []
[]\T1/txtt/m/sl/10 Model.train_datetime[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/1
0 Project.train_datetime[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 Model.

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[]\T1/qtm/m/n/10 Class \T1/txtt/m/n/10 FeatureEngineeringGraph \T1/qtm/m/n/10 h
as been re-moved. Use [][]\T1/txtt/m/sl/10 datarobot.models.
[947]
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[]\T1/qtm/m/n/10 Added a new method to trig-ger Fea-ture Im-pact cal-cu-la-tion
 for a Cus-tom In-fer-ence Im-age:
[948] [949]
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[]\T1/qtm/m/n/10 Added new ar-gu-ments \T1/txtt/m/n/10 explanation_algorithm \T
1/qtm/m/n/10 and \T1/txtt/m/n/10 max_explanations \T1/qtm/m/n/10 to method [][]
\T1/txtt/m/sl/10 Model.

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[]\T1/qtm/m/n/10 Added new ar-gu-ments \T1/txtt/m/n/10 explanation_algorithm \T
1/qtm/m/n/10 and \T1/txtt/m/n/10 max_explanations \T1/qtm/m/n/10 to method [][]
\T1/txtt/m/sl/10 Model.
[950]
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[]\T1/qtm/m/n/10 Batch Pre-dic-tion jobs now sup-port scor-ing to Azure and Goo
gle Cloud Stor-age with meth-ods
[951]
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[]\T1/qtm/m/n/10 These meth-ods now pro-vide ad-di-tional meta-data fields in F
ea-ture Im-pact re-sults if called with

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[]\T1/qtm/m/n/10 Sec-ondary dataset con-fig-u-ra-tion re-trieve and dele-tion i
s eas-ier now though new

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[][]\T1/txtt/m/sl/10 SecondaryDatasetConfigurations.delete[][] \T1/qtm/m/n/10 s
oft deletes a Sec-ondary dataset con-fig-u-ra-tion.
[952] [953]
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[]\T1/qtm/m/n/10 A new boolean at-tribute \T1/txtt/m/n/10 unsupervised_mode \T1
/qtm/m/n/10 was added to [][]\T1/txtt/m/sl/10 datarobot.
[954]
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[]\T1/qtm/m/n/10 Time se-ries model de-ploy-ments now sup-port pre-dic-tion in-
ter-vals. See

Underfull \hbox (badness 10000) in paragraph at lines 88650--88654
[][]\T1/txtt/m/sl/10 Deployment.get_prediction_intervals_settings[][] \T1/qtm/m
/n/10 and [][]\T1/txtt/m/sl/10 Deployment.

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[]\T1/qtm/m/n/10 It's now pos-si-ble to get fea-ture as-so-ci-a-tion sta-tuses 
for fea-turelists us-ing [][]\T1/txtt/m/sl/10 Project.

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[]\T1/qtm/m/n/10 Method [][]\T1/txtt/m/sl/10 Project.set_target[][] \T1/qtm/m/n
/10 sup-port new op-tional pa-ram-e-ters \T1/txtt/m/n/10 featureEngineeringGrap
hs \T1/qtm/m/n/10 and

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[]\T1/qtm/m/n/10 Se-ries ac-cu-racy re-trieval meth-ods ([][]\T1/txtt/m/sl/10 D
atetimeModel.get_series_accuracy_as_dataframe[][] \T1/qtm/m/n/10 and
[955] [956]
Underfull \hbox (badness 10000) in paragraph at lines 88830--88832
[]\T1/qtm/m/n/10 Mono-tonic con-straints are now sup-ported for OTV projects. T
o that end, the pa-ram-e-ters

Underfull \hbox (badness 10000) in paragraph at lines 88830--88832
\T1/txtt/m/n/10 monotonic_increasing_featurelist_id \T1/qtm/m/n/10 and \T1/txtt
/m/n/10 monotonic_decreasing_featurelist_id \T1/qtm/m/n/10 can be
[957] [958] [959]
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[]\T1/qtm/m/n/10 Pre-vi-ously avail-able for only Eu-reqa mod-els, Ad-vanced Tu
n-ing meth-ods and ob-jects, in-clud-ing

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[][]\T1/txtt/m/sl/10 Model.start_advanced_tuning_session[][]\T1/qtm/m/n/10 , []
[]\T1/txtt/m/sl/10 Model.get_advanced_tuning_parameters[][]\T1/qtm/m/n/10 , [][
]\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 89159--89161
[][][]\T1/txtt/m/sl/10 Project.upload_dataset[][] \T1/qtm/m/n/10 and [][]\T1/tx
tt/m/sl/10 Project.upload_dataset_from_data_source[][] \T1/qtm/m/n/10 will re-t
urn a
[960]
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[]\T1/qtm/m/n/10 New class for work-ing with model com-pli-ance doc-u-men-ta-ti
on fea-ture of DataRobot: class

Underfull \hbox (badness 10000) in paragraph at lines 89300--89305
[]\T1/qtm/m/n/10 Cross se-ries fea-tures can now be cre-ated within time se-rie
s mul-ti-series projects us-ing

Underfull \hbox (badness 10000) in paragraph at lines 89300--89305
\T1/qtm/m/n/10 the \T1/txtt/m/n/10 use_cross_series_features \T1/qtm/m/n/10 and
 \T1/txtt/m/n/10 aggregation_type \T1/qtm/m/n/10 at-tributes of the [][]\T1/txt
t/m/sl/10 datarobot.
[961]
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[]\T1/qtm/m/n/10 New \T1/txtt/m/n/10 number_of_known_in_advance_features \T1/qt
m/m/n/10 at-tribute has been added to the [][]\T1/txtt/m/sl/10 datarobot.

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[]\T1/qtm/m/n/10 Train-ing pre-dic-tions for date-time par-ti-tioned projects n
ow sup-port the new data sub-set
[962]
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[]\T1/qtm/m/n/10 New meth-ods and ob-jects, in-clud-ing [][]\T1/txtt/m/sl/10 Mo
del.start_advanced_tuning_session[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 Mode
l.

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\T1/txtt/m/sl/10 get_advanced_tuning_parameters[][]\T1/qtm/m/n/10 , [][]\T1/txt
t/m/sl/10 Model.advanced_tune[][]\T1/qtm/m/n/10 , and [][]\T1/txtt/m/sl/10 Adva
ncedTuningSession[][]\T1/qtm/m/n/10 , were

Underfull \hbox (badness 10000) in paragraph at lines 89444--89447
[]\T1/qtm/m/n/10 A cus-tom pre-dic-tion thresh-old may now be con-fig-ured for 
each model via [][]\T1/txtt/m/sl/10 Model.

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[]\T1/qtm/m/n/10 In-di-vid-ual cross val-i-da-tion scores can be re-trieved for
 new mod-els us-ing [][]\T1/txtt/m/sl/10 Model.

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[][][]\T1/txtt/m/sl/10 ModelRecommendation.get[][] \T1/qtm/m/n/10 now ac-cepts 
an op-tional pa-ram-e-ter of type \T1/txtt/m/n/10 datarobot.enums.
[963]
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[]\T1/qtm/m/n/10 Added a new fea-ture to re-trieve fea-ture logs for time se-ri
es projects. Check [][]\T1/txtt/m/sl/10 datarobot.

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\T1/txtt/m/sl/10 DatetimePartitioning.feature_log_list()[][] \T1/qtm/m/n/10 and
 [][]\T1/txtt/m/sl/10 datarobot.DatetimePartitioning.
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[976]
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[]\T1/qtm/m/n/10 In sev-eral places where \T1/txtt/m/n/10 AppPlatformError \T1/
qtm/m/n/10 was be-ing raised, now \T1/txtt/m/n/10 TypeError\T1/qtm/m/n/10 , \T1
/txtt/m/n/10 ValueError \T1/qtm/m/n/10 or

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[]\T1/qtm/m/n/10 If a \T1/txtt/m/n/10 ClientError \T1/qtm/m/n/10 or \T1/txtt/m/
n/10 ServerError \T1/qtm/m/n/10 oc-curs dur-ing a call to \T1/txtt/m/n/10 Proje
ct.from_async\T1/qtm/m/n/10 , then a
[977]
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[]\T1/txtt/m/n/10 recommendation_settings \T1/qtm/m/n/10 pa-ram-e-ter of \T1/tx
tt/m/n/10 Project.start \T1/qtm/m/n/10 is dep-re-cated in fa-vor of
[978] [979] [980] [981] [982] (./datarobot-public-api-client.ind [983] [984]
[985]
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[]\T1/txtt/m/n/10 bucket_sample_sizes \T1/qtm/m/n/10 (\T1/qtm/m/it/10 datarobot
.models.deployment.custom_metrics.CustomMetricValuesOverBatch prop-erty\T1/qtm/
m/n/10 ),

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[]\T1/txtt/m/n/10 bucket_sample_sizes \T1/qtm/m/n/10 (\T1/qtm/m/it/10 datarobot
.models.deployment.custom_metrics.CustomMetricValuesOverTime prop-erty\T1/qtm/m
/n/10 ),
[986] [987] [988] [989] [990] [991]
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[]\T1/txtt/m/n/10 find_anomalous_regions() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 data
robot.models.anomaly_assessment.AnomalyAssessmentPredictionsPreview
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[]\T1/txtt/m/n/10 get_buckets_as_dataframe() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.deployment.custom_metrics.CustomMetricValuesOverBatch

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[]\T1/txtt/m/n/10 get_buckets_as_dataframe() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.deployment.custom_metrics.CustomMetricValuesOverTime
[997]
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[]\T1/txtt/m/n/10 get_document_page_with_text_locations() \T1/qtm/m/n/10 (\T1/q
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e

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[]\T1/txtt/m/n/10 get_explanations_data_in_regions() \T1/qtm/m/n/10 (\T1/qtm/m/
it/10 datarobot.models.anomaly_assessment.AnomalyAssessmentRecord
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[]\T1/txtt/m/n/10 is_model_compliance_initialized \T1/qtm/m/n/10 (\T1/qtm/m/it/
10 datarobot.models.automated_documentation.AutomatedDocument prop-
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[]\T1/txtt/m/n/10 list_available_document_types() \T1/qtm/m/n/10 (\T1/qtm/m/it/
10 datarobot.models.automated_documentation.AutomatedDocument class
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[]\T1/txtt/m/n/10 validate_task_parameters() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.user_blueprints.models.UserBlueprintValidateTaskParameters
[1013]) [1014] (./datarobot-public-api-client.aux)

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[1] [2] [1] [2]
Chapter 1.
[3] [4]
Chapter 2.
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[][][]\T1/txtt/m/sl/10 Dataset.create_from_url[][] \T1/qtm/m/n/10 takes .csv da
ta from a URL. If you have set

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[][][]\T1/txtt/m/sl/10 Dataset.create_from_data_source[][] \T1/qtm/m/n/10 takes
 data from a data source. If you have set
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[12] [13] [14] [15] [16]
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[18] [19] [20] [21] [22]
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[23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36]
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[]\T1/qtm/m/n/10 For mul-ti-class mod-els, you can get a list of per-class lift
 charts us-ing the \T1/txtt/m/n/10 Model \T1/qtm/m/n/10 method

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[]\T1/qtm/m/n/10 Just as with the lift and ROC charts, you can use \T1/txtt/m/n
/10 Model \T1/qtm/m/n/10 meth-ods \T1/txtt/m/n/10 get_residuals_chart \T1/qtm/m
/n/10 and
[37] [38] [39] [40] [41] [42] [43] [44]
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[]\T1/qtm/m/n/10 gap_duration (str): A du-ra-tion string such as those re-turne
d by the [][]\T1/txtt/m/sl/10 partitioning_methods.
[45]
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\T1/qtm/m/n/10 and \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 . Us-ing
 the same date for both \T1/txtt/m/n/10 primary_training_end_date \T1/qtm/m/n/1
0 and
[46]
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[]\T1/qtm/m/n/10 For date-time par-ti-tioned model you can re-trieve the Ac-cu-
racy over Time plot. To do so use

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[][]\T1/txtt/m/sl/10 DatetimeModel.get_accuracy_over_time_plot[][]\T1/qtm/m/n/1
0 . You can also re-trieve the de-tailed meta-data us-ing
[47] [48] [49] [50] [51]
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[]\T1/qtm/m/n/10 Enough rows of his-tor-i-cal data must be pro-vided to cover t
he span of the ef-fec-tive Fea-ture Deriva-
[52] [53] [54] [55]
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[]\T1/qtm/m/n/10 Pre-dic-tion in-ter-vals can be cal-cu-lated for a [][]\T1/txt
t/m/sl/10 DatetimeModel[][] \T1/qtm/m/n/10 us-ing the [][]\T1/txtt/m/sl/10 Date
timeModel.
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[]\T1/qtm/m/n/10 1. Up-load a pre-dic-tion dataset, spec-i-fy-ing \T1/txtt/m/n/
10 predictions_start_date\T1/qtm/m/n/10 , \T1/txtt/m/n/10 predictions_end_date\
T1/qtm/m/n/10 , and
[71]
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[]\T1/qtm/m/n/10 Up-load a pre-dic-tion dataset that con-tains la-bel col-umn(s
), re-quest com-pute ex-ter-nal test on one of
[72] [73] [74] [75] [76] [77] [78] [79] [80]

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\T1/qtm/b/n/10 Note:  \T1/txtt/m/n/10 PredictionExplanations.get_all_as_datafra
me() \T1/qtm/m/n/10 and \T1/txtt/m/n/10 PredictionExplanations.
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[]\T1/qtm/m/n/10 If you just want to get gen-er-ated pre-dic-tions from a Pre-d
ic-tJob, you can use the \T1/txtt/m/n/10 PredictJob.
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[]\T1/qtm/m/n/10 In or-der to sched-ule the ex-e-cu-tion of a Batch Pre-dic-tio
n job, a def-i-ni-tion must first be cre-ated, us-
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[]\T1/qtm/m/n/10 Job def-i-ni-tions are only be ex-e-cuted by the sched-uler if
 \T1/txtt/m/n/10 enabled \T1/qtm/m/n/10 is set to \T1/txtt/m/n/10 True\T1/qtm/m
/n/10 . If you have a

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[]\T1/qtm/m/n/10 When cre-at-ing a new de-ploy-ment, a DataRobot \T1/txtt/m/n/1
0 registered_model_version_id\TS1/txtt/m/n/10 ``\T1/txtt/m/n/10 (also known as
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\T1/qtm/m/n/10 of [][]\T1/txtt/m/sl/10 datarobot.models.deployment.DeploymentGr
antSharedRoleWithId[][] \T1/qtm/m/n/10 and [][]\T1/txtt/m/sl/10 datarobot.model
s.
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[]\T1/qtm/m/n/10 Re-fer to [][]\T1/txtt/m/sl/10 ExecutionEnvironment[][] \T1/qt
m/m/n/10 for prop-er-ties of the ex-e-cu-tion en-vi-ron-ment ob-ject and
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[]\T1/qtm/m/n/10 cus-tom_model.update(is_training_data_for_versions_permanently
_enabled=True) cus-
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[]\T1/qtm/m/n/10 To cre-ate a hosted cus-tom met-ric job from gallery tem-plate
, use \T1/qtm/m/it/10 dr.registry.Job.create_from_custom_metric_gallery_templat
e\T1/qtm/m/n/10 ,
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[]\T1/qtm/m/n/10 You can also fil-ter the reg-is-tered model ver-sions that are
 re-turned by pass-ing an in-stance of the
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[]\T1/qtm/m/n/10 Use Cases sup-port \T1/txtt/m/n/10 SHARING_ROLE.OWNER\T1/qtm/m
/n/10 , \T1/txtt/m/n/10 SHARING_ROLE.EDITOR\T1/qtm/m/n/10 , \T1/txtt/m/n/10 SHA
RING_ROLE.CONSUMER \T1/qtm/m/n/10 and
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\T1/qtm/m/n/10 (New in ver-sion v2.23) one of \T1/txtt/m/n/10 datarobot.enums.

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\T1/qtm/m/n/10 ness. Can be one of \T1/txtt/m/n/10 proportionalParity\T1/qtm/m/
n/10 , \T1/txtt/m/n/10 equalParity\T1/qtm/m/n/10 ,

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\T1/txtt/m/n/10 predictionBalance\T1/qtm/m/n/10 , \T1/txtt/m/n/10 trueFavorable
AndUnfavorableRateParity \T1/qtm/m/n/10 or
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\T1/qtm/m/it/10 **record_kwargs\T1/txtt/m/n/10 )|  
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\T1/qtm/m/n/10 [string] The URL for the pre-dic-tion dataset (e.g.:

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\T1/qtm/m/n/10 [string] The URL for the scored dataset (e.g.: \T1/qtm/m/it/10 h
ttps://storage_account.blob.endpoint/container/blob_name\T1/qtm/m/n/10 ) 
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\T1/qtm/m/n/10 [string] The URL for the pre-dic-tion dataset (e.g.:

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\T1/qtm/m/n/10 [string] The URL for the scored dataset (e.g.: \T1/qtm/m/it/10 h
ttp(s)://storage.googleapis.com/[bucket]/[object]\T1/qtm/m/n/10 ) 
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[]\T1/qtm/m/n/10 par-ti-tion : sub-set of train-ing data to score, one of \T1/t
xtt/m/n/10 datarobot.enums.
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\T1/qtm/m/it/10 tered_model_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 tered_model_version\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 mlpkg_file_contents=None\T1/txtt/m/n/10 )|  
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\T1/qtm/m/it/10 ment_attribute=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/n/10 Cre-ate a hosted cus-tom met-ric from a tem-plate. A short-cut f
or 2 calls:
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\T1/qtm/m/it/10 is_model_specific\T1/qtm/m/n/10 , 
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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.REGRESSION\T1/qtm/m/n/10 , \T1/qtm/m/it/1
0 datarobot.TARGET_TYPE.MULTICLASS\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED\T1/qtm/m/n/10 , \T1/qtm/m/it
/10 datarobot.TARGET_TYPE.ANOMALY\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED \T1/qtm/m/n/10 or \T1/qtm/m/
it/10 datarobot.TARGET_TYPE.ANOMALY
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.REGRESSION\T1/qtm/m/n/10 , \T1/qtm/m/it/1
0 datarobot.TARGET_TYPE.MULTICLASS\T1/qtm/m/n/10 ,

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\T1/qtm/m/it/10 datarobot.TARGET_TYPE.UNSTRUCTURED\T1/qtm/m/n/10 , \T1/qtm/m/it
/10 datarobot.TARGET_TYPE.TEXT_GENERATION\T1/qtm/m/n/10 ] 

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n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 the type of the im-age, ei-ther CUS-TOM_MODEL_IMAGE_TYPE.CUSTOM_
MODEL_IMAGE

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\T1/qtm/m/n/10 if the test-ing at-tempt is us-ing a Cus-tom-Mod-e-lIm-age as it
s model or CUS-
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,

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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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\T1/qtm/m/n/10 The base en-vi-ron-ment to use with this model ver-sion. At leas
t one of

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\T1/qtm/m/n/10 ^^Pfile1.txt^^Q), (^^P/home/user/Documents/myModel/folder/file2.
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RESS_POLICY.NONE\T1/qtm/m/n/10 ,
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Underfull \hbox (badness 10000) in paragraph at lines 26700--26704
\T1/qtm/m/n/10 The base en-vi-ron-ment to use with this model ver-sion. At leas
t one of

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\T1/qtm/m/n/10 will be used for tu-ples Ex-am-ple: [(^^P/home/user/Documents/my
Model/file1.txt^^Q,

Underfull \hbox (badness 10000) in paragraph at lines 26725--26735
\T1/qtm/m/n/10 ^^Pfile1.txt^^Q), (^^P/home/user/Documents/myModel/folder/file2.
txt^^Q,

Underfull \hbox (badness 10000) in paragraph at lines 26725--26735
\T1/qtm/m/n/10 ^^Pfolder/file2.txt^^Q)] or [^^P/home/user/Documents/myModel/fil
e1.txt^^Q,

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\T1/qtm/m/n/10 De-ter-mines whether the given cus-tom model is iso-lated, or ca
n ac-cess the

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\T1/qtm/m/n/10 pub-lic net-work. Val-ues: [\T1/qtm/m/it/10 datarobot.NETWORK_EG
RESS_POLICY.NONE\T1/qtm/m/n/10 ,
[347]
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\T1/qtm/m/n/10 build sta-tus of the ex-e-cu-tion en-vi-ron-ment ver-sion to fil
-ter by. See

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\T1/qtm/m/n/10 datarobot.enums.EXECUTION_ENVIRONMENT_VERSION_BUILD_STATUS
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Underfull \hbox (badness 10000) in paragraph at lines 28625--28629
\T1/qtm/m/n/10 whether anomaly pre-dic-tions should be cal-i-brated to be be-tw
een 0

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\T1/qtm/m/n/10 and 1 by DR. only ap-plies to cus-tom es-ti-ma-tors with tar-get
 type
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[376] [377] [378] [379] [380] [381]
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\T1/qtm/m/n/10 [str] Op-tional. The full JDBC URL (for ex-am-ple:

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\T1/qtm/m/n/10 [str] Op-tional. The iden-ti-fier of the Con-nec-tor. if the typ
e is Data-S-tore-

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\T1/qtm/m/n/10 [str] Op-tional. The full JDBC URL (for ex-am-ple:
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\T1/qtm/m/n/10 SCHEMA . TABLE _ NAME$[][]' - `[][]$jdbc : DATA _ SOURCE _ GIVEN
 _ NAME$[][]/<query>' - for
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\T1/qtm/m/it/10 only_matched_predictions=None\T1/qtm/m/n/10 , 
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 The res-o-lu-tion that is used for bin-ning. One of \T1/txtt/m/n
/10 datarobot.enums.
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\T1/qtm/m/n/10 [list] To cre-ate or up-date ex-ist-ing seg-ment anal-y-sis at-t
ributes, see
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\T1/qtm/m/n/10 [bool] If pre-dic-tions data col-lec-tion is en-abled for this d
e-ploy-

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\T1/qtm/m/n/10 ment. To up-date ex-ist-ing `'pre-dic-tions_data_collection'' se
t-tings, see
[449]
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\T1/qtm/m/n/10 [bool] If tar-get pre-dic-tion_warning is en-abled for this de-p
loy-ment.

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\T1/qtm/m/n/10 To cre-ate or up-date ex-ist-ing `'pre-dic-tion_warning'' set-ti
ngs, see
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\T1/qtm/m/it/10 tected_feature=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 ness_threshold=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 model_package_id=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 able_target_outcome=None\T1/txtt/m/n/10 )|  
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[]\T1/qtm/m/it/10 baseline_validation_job_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 project_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 log_version_id\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 time_partition_column\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 is_external_baseline_dataset_valid\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 series_id_columns=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 out_start_date=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 out_end_date=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 tests=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 cast_window_start=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 cast_window_end=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 sage=None\T1/txtt/m/n/10 )|  
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[]\T1/qtm/m/n/10 {`key':'DataRobot', `sum-mary':{`min':0, `max':29815.0, `std-D
ev':6498.029,
[491] [492] [493] [494] [495]
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[]\T1/qtm/m/n/10 {`key':'DataRobot', `sum-mary':{`min':0, `max':29815.0, `std-D
ev':6498.029,
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Underfull \hbox (badness 10000) in paragraph at lines 42429--42432
[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0,B=1) can be re-trieved via:

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\T1/txtt/m/n/10 pairwise_joint_probabilities.statistic_dataframes[(0,1)].loc[\T
S1/txtt/m/n/10 '\T1/txtt/m/n/10 A\TS1/txtt/m/n/10 '\T1/txtt/m/n/10 ,

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[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0,B=1) can be re-trieved via:
[502]
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\T1/qtm/m/n/10 [list(dict)] List of con-di-tional prob-a-bil-ity val-ues with a
 schema de-scribed as

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[]\T1/qtm/m/n/10 E.g. The prob-a-bil-ity P(A=0|B=1) can be re-trieved via:

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\T1/txtt/m/n/10 pairwise_conditional_probabilities.statistic_dataframes[(0,1)].

[503] [504]
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\T1/qtm/m/n/10 [enums.FEATURE_ASSOCIATION_METRIC] The name of a met-ric to

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\T1/qtm/m/n/10 get pair-wise data for. Since `v2.19' this is op-tional and de-f
aults to

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\T1/qtm/m/n/10 [enums.FEATURE_ASSOCIATION_TYPE] The type of de-pen-

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\T1/qtm/m/n/10 dence for the data. Since `v2.19' this is op-tional and de-fault
s to
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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
[514]
Underfull \hbox (badness 10000) in paragraph at lines 43559--43563
\T1/qtm/m/n/10 Time unit of the pre-dic-tion point round-ing. One of \T1/txtt/m
/n/10 datarobot.enums.

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\T1/qtm/m/n/10 Time unit of the fea-ture deriva-tion win-dow. One of \T1/txtt/m
/n/10 datarobot.enums.
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[]\T1/qtm/m/it/10 ff_metadata_datetime_per_backtest\T1/txtt/m/n/10 )|  
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 48881--48886
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[564] [565] [566] [567] [568] [569]
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.
[570]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 49537--49542
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 55200--55205
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[624] [625] [626] [627] [628] [629]
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.

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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[630] [631] [632] [633] [634]
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\T1/qtm/m/n/10 of the \T1/txtt/m/n/10 windows_basis_unit \T1/qtm/m/n/10 into th
e past rel-a-tive to the fore-cast point the

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\T1/txtt/m/n/10 feature_derivation_window_start \T1/qtm/m/n/10 set on the proje
ct due to the dif-fer-enc-ing
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

Underfull \hbox (badness 8075) in paragraph at lines 56601--56606
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[639] [640] [641] [642] [643] [644] [645] [646] [647] [648] [649]
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\T1/qtm/m/n/10 [AnomalyOverTimePlotPreview] a [][]\T1/txtt/m/sl/10 AnomalyOverT
imePlotPreview[][] \T1/qtm/m/n/10 rep-re-sent-ing
[650]
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\T1/qtm/m/n/10 [list of Anoma-lyAssess-men-tRecord] a [][]\T1/txtt/m/sl/10 Anom
alyAssessmentRecord[][] \T1/qtm/m/n/10 rep-re-sent-ing
[651]
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\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Lift chart data source. Ch
eck

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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Lift chart data source. Ch
eck
[654]
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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) Roc Curve data source. Che
ck

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\T1/qtm/m/n/10 [str] (Dep-re-cated in ver-sion v3.4) ROC curve data source. Che
ck
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[667] [668] [669]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 59878--59883
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[670] [671] [672] [673]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 60185--60190
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[674] [675] [676] [677] [678] [679] [680] [681] [682] [683] [684] [685]
[686] [687] [688] [689]
Underfull \hbox (badness 5359) in paragraph at lines 61731--61734
\T1/qtm/m/n/10 keys: \T1/txtt/m/n/10 featureName\T1/qtm/m/n/10 , \T1/txtt/m/n/1
0 impactNormalized\T1/qtm/m/n/10 , and \T1/txtt/m/n/10 impactUnnormalized\T1/qt
m/m/n/10 , and
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 63071--63076
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[701] [702] [703] [704] [705] [706] [707]
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
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Underfull \hbox (badness 10000) in paragraph at lines 63679--63685
\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.

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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
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Underfull \hbox (badness 8075) in paragraph at lines 63727--63732
[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[708] [709] [710] [711] [712] [713] [714] [715] [716] [717] [718]
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\T1/qtm/m/it/10 low_partial_history_time_series_predictions=False\T1/qtm/m/n/10
 , 

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[]\T1/qtm/m/n/10 This is the spec-i-fi-ca-tion that should be passed to [][]\T1
/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the
[719]
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[]\T1/qtm/m/n/10 Note that ei-ther (\T1/txtt/m/n/10 holdout_start_date\T1/qtm/m
/n/10 , \T1/txtt/m/n/10 holdout_duration\T1/qtm/m/n/10 ) or (\T1/txtt/m/n/10 ho
ldout_start_date\T1/qtm/m/n/10 ,

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\T1/qtm/m/n/10 [str] one of \T1/txtt/m/n/10 datarobot.enums.DATETIME_AUTOPILOT_
DATA_SELECTION_METHOD\T1/qtm/m/n/10 .

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\T1/qtm/m/n/10 [datetime.datetime or None] The start date of hold-out scor-ing 
data. If
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[]\T1/qtm/m/n/10 Op-tion 2 (New in ver-sion v2.20): Use \T1/txtt/m/n/10 index\T
1/qtm/m/n/10 , \T1/txtt/m/n/10 primary_training_start_date\T1/qtm/m/n/10 ,
[723] [724] [725]
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\T1/qtm/m/n/10 [str] one of \T1/txtt/m/n/10 datarobot.enums.DATETIME_AUTOPILOT_
DATA_SELECTION_METHOD\T1/qtm/m/n/10 .
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\T1/qtm/m/n/10 proach for spec-i-fy-ing back-tests (\T1/txtt/m/n/10 gap_duratio
n\T1/qtm/m/n/10 , \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 , and
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[]\T1/qtm/m/n/10 This is the spec-i-fi-ca-tion that should be passed to [][]\T1
/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the

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\T1/txtt/m/n/10 partitioning_method \T1/qtm/m/n/10 pa-ram-e-ter. To see the ful
l par-ti-tion-ing use [][]\T1/txtt/m/sl/10 DatetimePartitioning.
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\T1/qtm/m/n/10 [bool] De-fault \T1/txtt/m/n/10 False\T1/qtm/m/n/10 . If \T1/txt
t/m/n/10 False\T1/qtm/m/n/10 , will use a duration-based ap-proach

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\T1/qtm/m/n/10 for spec-i-fy-ing back-tests (\T1/txtt/m/n/10 gap_duration\T1/qt
m/m/n/10 , \T1/txtt/m/n/10 validation_start_date\T1/qtm/m/n/10 , and

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\T1/qtm/m/n/10 ing back-tests (\T1/txtt/m/n/10 primary_training_start_date\T1/q
tm/m/n/10 , \T1/txtt/m/n/10 primary_training_end_date\T1/qtm/m/n/10 ,
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[748]
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[]\T1/qtm/m/n/10 Com-pute a Pre-dic-tion-Ex-pla-na-tion-sIni-tial-iza-tion for 
the model via \T1/txtt/m/n/10 datarobot.

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[]\T1/qtm/m/n/10 Com-pute pre-dic-tions for the model and dataset via \T1/txtt/
m/n/10 datarobot.Model.
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\T1/qtm/m/n/10 Cre-ate pre-dic-tion ex-pla-na-tions for the the dataset used to
 train the model. This can be

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\T1/qtm/m/n/10 re-trieved by call-ing \T1/txtt/m/n/10 dr.Model.get().featurelis
t_id\T1/qtm/m/n/10 . For OTV and time-series projects,

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[]\T1/qtm/m/n/10 Com-pute a Pre-dic-tion-Ex-pla-na-tion-sIni-tial-iza-tion for 
the model via \T1/txtt/m/n/10 datarobot.

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[]\T1/qtm/m/n/10 Com-pute pre-dic-tions for the model and dataset via \T1/txtt/
m/n/10 datarobot.Model.
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\T1/qtm/m/it/10 tion_explanations=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 justed_prediction=None\T1/qtm/m/n/10 , 

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\T1/qtm/m/it/10 justed_prediction_values=None\T1/txtt/m/n/10 )|  

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\T1/qtm/m/it/10 ment_method=None\T1/txtt/m/n/10 )|  
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[]\T1/qtm/m/n/10 Project.list(search_params={`project_name': `red'}) >>> [Proje
ct(`Prediction Time'),
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\T1/qtm/m/n/10 [ClassMappingAggregationSettings, op-tional] In-stance of \T1/tx
tt/m/n/10 datarobot.helpers.
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\T1/qtm/m/n/10 level: \T1/qtm/m/it/10 mono-tonic_increasing_featurelist_id\T1/q
tm/m/n/10 , \T1/qtm/m/it/10 mono-tonic_decreasing_featurelist_id\T1/qtm/m/n/10 
,

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\T1/qtm/m/it/10 sup-ports_composable_ml \T1/qtm/m/n/10 and \T1/qtm/m/it/10 sup-
ports_monotonic_constraints\T1/qtm/m/n/10 . Fol-low-ing at-

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\T1/qtm/m/n/10 tributes are ab-sent and could be re-trieved from the in-di-vid-
ual model level:

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\T1/qtm/m/it/10 has_empty_clusters\T1/qtm/m/n/10 , \T1/qtm/m/it/10 is_n_cluster
s_dynamically_determined\T1/qtm/m/n/10 , \T1/qtm/m/it/10 pre-dic-tion_threshold

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\T1/qtm/m/n/10 Raised if \T1/txtt/m/n/10 forecast_point \T1/qtm/m/n/10 or \T1/t
xtt/m/n/10 predictions_start_date \T1/qtm/m/n/10 and
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\T1/qtm/m/n/10 of fea-tures with a mono-ton-i-cally de-creas-ing re-la-tion-shi
p to the tar-get. Pass-

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\T1/qtm/m/n/10 ing \T1/txtt/m/n/10 None \T1/qtm/m/n/10 dis-ables de-creas-ing m
ono-tonic-ity con-straint. De-fault (\T1/txtt/m/n/10 dr.enums.
[799]
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[]\T1/qtm/m/n/10 All du-ra-tions should be spec-i-fied with a du-ra-tion string
 such as those re-turned by the

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[][]\T1/txtt/m/sl/10 partitioning_methods.construct_duration_string[][] \T1/qtm
/m/n/10 helper method. Please see [][]\T1/qtm/m/it/10 date-time
[800] [801] [802] [803] [804] [805] [806]
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\T1/qtm/m/n/10 (New in ver-sion v2.23) one of \T1/txtt/m/n/10 datarobot.enums.

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\T1/txtt/m/n/10 DATETIME_AUTOPILOT_DATA_SAMPLING_METHOD\T1/qtm/m/n/10 . Ap-pli-
ca-ble for OTV projects
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\T1/qtm/m/n/10 (New in ver-sion v2.24) Met-ric to use for cal-cu-lat-ing fair-

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\T1/qtm/m/n/10 ness. Can be one of \T1/txtt/m/n/10 proportionalParity\T1/qtm/m/
n/10 , \T1/txtt/m/n/10 equalParity\T1/qtm/m/n/10 ,

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\T1/txtt/m/n/10 predictionBalance\T1/qtm/m/n/10 , \T1/txtt/m/n/10 trueFavorable
AndUnfavorableRateParity \T1/qtm/m/n/10 or
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\T1/qtm/m/n/10 [PartitioningMethod, op-tional] An in-stance of \T1/txtt/m/n/10 
datarobot.helpers.
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\T1/qtm/m/n/10 If value of \T1/txtt/m/n/10 variable_type \T1/qtm/m/n/10 is not 
from \T1/txtt/m/n/10 datarobot.enums.
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\T1/qtm/m/n/10 In-stance of the Date-timePar-ti-tion-ing de-fined in \T1/txtt/m
/n/10 datarobot.helpers.
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[]\T1/qtm/m/n/10 This is an al-ter-na-tive to pass-ing a spec-i-fi-ca-tion to [
][]\T1/txtt/m/sl/10 Project.analyze_and_model[][] \T1/qtm/m/n/10 via the
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\T1/qtm/m/n/10 [Optional[RegisteredModelVersionsListFilters]] A Reg-is-tered-Mo
d-elVer-sion-sList-Fil-ters
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[]\T1/qtm/m/n/10 Added a new class :class: \T1/qtm/m/it/10 Eval-u-a-tion-Datase
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[]\T1/qtm/m/n/10 Added a new class :class: \T1/qtm/m/it/10 Eval-u-a-tion-Datase
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[921]
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\T1/txtt/m/sl/10 run[][] [][]BatchMonitoringJob.get_status[][] [][]BatchMonitor
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[]\T1/qtm/m/n/10 Added [][]\T1/txtt/m/sl/10 DatetimePartitioningId[][]\T1/qtm/m
/n/10 , which can be passed as a \T1/qtm/m/it/10 par-ti-tion-ing_method \T1/qtm
/m/n/10 to [][]\T1/txtt/m/sl/10 Project.

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\T1/txtt/m/sl/10 create_from_url[][] [][]Dataset.create_from_data_source[][] []
[]Dataset.create_from_query_generator[][]

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[][]\T1/txtt/m/sl/10 Dataset.create_project[][] [][]Project.create[][] [][]Proj
ect.create_from_data_source[][] [][]Project.

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[922]
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[]\T1/qtm/m/n/10 If the user con-fig-ures the client via env vars, then set the
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[]\T1/qtm/m/n/10 Added method meth:\T1/qtm/m/it/10 Deployment.get_predictions_o
ver_time <datarobot.models.Deployment.get_predictions_over_time>

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\T1/txtt/m/sl/10 request_feature_effect[][] [][]Model.get_or_request_feature_ef
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[][]\T1/txtt/m/sl/10 Model.get_all_lift_charts[][] [][]Model.get_residuals_char
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[][]\T1/txtt/m/sl/10 Model.request_lift_chart[][] [][]Model.request_residuals_c
hart[][] [][]Model.get_roc_curve[][] [][]Model.
[923]
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[]\T1/qtm/m/n/10 Added new method for re-triev-ing all avail-able fea-ture im-p
acts for the model [][]\T1/txtt/m/sl/10 Model.

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\T1/txtt/m/sl/10 PredictionExplanations.get_all_as_dataframe()[][] \T1/qtm/m/n/
10 and [][]\T1/txtt/m/sl/10 datarobot.PredictionExplanations.
[924]
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[]\T1/qtm/m/n/10 The sliced in-sight API end-point \T1/qtm/m/it/10 GET: api/v2/
insights/<insight_name>/ \T1/qtm/m/n/10 re-turns a pag-i-nated re-

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[]\T1/txtt/m/n/10 DatetimeModel.get_feature_fit_metadata \T1/qtm/m/n/10 has bee
n re-moved. Use [][]\T1/txtt/m/sl/10 DatetimeModel.

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[]\T1/txtt/m/n/10 DatetimeModel.request_feature_fit \T1/qtm/m/n/10 has been re-
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[]\T1/txtt/m/n/10 Model.get_or_request_feature_fit \T1/qtm/m/n/10 has been re-m
oved. Use [][]\T1/txtt/m/sl/10 Model.

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[]\T1/txtt/m/n/10 DatetimeModel.get_or_request_feature_fit \T1/qtm/m/n/10 has b
een re-moved. Use [][]\T1/txtt/m/sl/10 DatetimeModel.

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[]\T1/qtm/m/n/10 Dep-re-cated the fol-low-ing meth-ods for re-triev-ing [][]\T1
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/sl/10 DataStore.
[925]

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[926]
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[]\T1/qtm/m/n/10 Added new meth-ods [][]\T1/txtt/m/sl/10 BatchPredictionJob.app
ly_time_series_data_prep_and_score[][] \T1/qtm/m/n/10 and

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[][]\T1/txtt/m/sl/10 BatchPredictionJob.apply_time_series_data_prep_and_score_t
o_file[][] \T1/qtm/m/n/10 that ap-ply time se-ries

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[]\T1/qtm/m/n/10 Added new meth-ods [][]\T1/txtt/m/sl/10 DataEngineQueryGenerat
or.prepare_prediction_dataset[][] \T1/qtm/m/n/10 and

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[][]\T1/txtt/m/sl/10 DataEngineQueryGenerator.prepare_prediction_dataset_from_c
atalog[][] \T1/qtm/m/n/10 that ap-ply time se-ries

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[]\T1/qtm/m/n/10 Added two new meth-ods to the Im-ageAug-men-ta-tion-List class
: [][]\T1/txtt/m/sl/10 ImageAugmentationList.list[][]\T1/qtm/m/n/10 ,
[927] [928] [929]
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[]\T1/qtm/m/n/10 Added sup-port for cre-at-ing mono-tonic fea-ture lists for ti
me se-ries projects. Set

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[]\T1/qtm/m/n/10 Added in-for-ma-tion about ver-tex to ad-vanced tun-ing pa-ram
-e-ters [][]\T1/txtt/m/sl/10 datarobot.models.Model.
[930]
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[][][]\T1/txtt/m/sl/10 CustomModelVersion[][]\T1/qtm/m/n/10 's \T1/txtt/m/n/10 
required_metadata \T1/qtm/m/n/10 pa-ram-e-ter has been re-moved. Use

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[][][]\T1/txtt/m/sl/10 CustomTaskVersion[][]\T1/qtm/m/n/10 's \T1/txtt/m/n/10 r
equired_metadata \T1/qtm/m/n/10 pa-ram-e-ter has been re-moved. Use

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[]\T1/qtm/m/n/10 The [][]\T1/txtt/m/sl/10 Deployment[][] \T1/qtm/m/n/10 method 
\T1/txtt/m/n/10 create_from_custom_model_image \T1/qtm/m/n/10 was re-moved. Use
 [][]\T1/txtt/m/sl/10 Deployment.
[931]
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[]\T1/qtm/m/n/10 Added ex-per-i-men-tal sup-port to re-trieve doc-u-ment text e
x-trac-tion sam-ples us-

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\T1/qtm/m/n/10 ing: - [][]\T1/txtt/m/sl/10 DocumentTextExtractionSample[][] \T1
/qtm/m/n/10 - [][]\T1/txtt/m/sl/10 DocumentTextExtractionSamplePage[][] \T1/qtm
/m/n/10 -

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[]\T1/qtm/m/n/10 Added sup-port to pass cal-cu-la-tion mode to pre-dic-tion ex-
pla-na-tions (\T1/qtm/m/it/10 mode \T1/qtm/m/n/10 pa-ram-e-ter in
[932]
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\T1/qtm/m/n/10 - [][]\T1/txtt/m/sl/10 Project.apply_bias_mitigation[][] \T1/qtm
/m/n/10 - [][]\T1/txtt/m/sl/10 Project.request_bias_mitigation_feature_info[][]


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\T1/qtm/m/n/10 - [][]\T1/txtt/m/sl/10 Project.get_bias_mitigation_feature_info[
][] \T1/qtm/m/n/10 and by adding new bias mit-

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\T1/qtm/m/n/10 i-ga-tion params - bias_mitigation_feature_name - bias_mitigatio
n_technique - in-

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\T1/qtm/m/n/10 clude_bias_mitigation_feature_as_predictor_variable to the ex-is
t-ing method - [][]\T1/txtt/m/sl/10 Project.start[][] \T1/qtm/m/n/10 and

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\T1/qtm/m/n/10 by adding this enum to sup-ply params to some of the above func-
tion-al-ity \T1/txtt/m/n/10 datarobot.enums.
[933]
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[]\T1/qtm/m/n/10 Up-date the doc-u-men-ta-tion to sug-gest that \T1/qtm/m/it/10
 fea-ture_derivation_window_end \T1/qtm/m/n/10 of [][]\T1/txtt/m/sl/10 datarobo
t.

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[]\T1/qtm/m/n/10 Added the abil-ity to turn off su-per-vised fea-ture re-duc-ti
on for Time Se-ries projects. Op-tion
[934] [935]
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[]\T1/txtt/m/n/10 DatetimeModel.get_feature_fit <datarobot.models.DatetimeModel
.

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[]\T1/qtm/m/n/10 Dep-re-cat-ing sca-le-out pa-ram-e-ters for projects / mod-els
. In-cludes \T1/txtt/m/n/10 scaleout_modeling_mode\T1/qtm/m/n/10 ,
[936]
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[]\T1/qtm/m/n/10 Added the abil-ity to up-load a pre-dic-tion dataset into a pr
oject from the AI cat-a-log [][]\T1/txtt/m/sl/10 Project.
[937]
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[]\T1/qtm/m/n/10 Added the abil-ity to con-trol class map-ping ag-gre-ga-tion i
n mul-ti-class projects via

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[]\T1/qtm/m/n/10 Added the abil-ity to com-pute and re-trieve Fea-ture Ef-fects
 for a Mul-ti-class model us-

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\T1/qtm/m/n/10 ing [][]\T1/txtt/m/sl/10 datarobot.models.Model.request_feature_
effects_multiclass()[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 datarobot.

Underfull \hbox (badness 10000) in paragraph at lines 86642--86650
\T1/txtt/m/sl/10 models.Model.get_feature_effects_multiclass()[][] \T1/qtm/m/n/
10 or [][]\T1/txtt/m/sl/10 datarobot.models.Model.

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\T1/txtt/m/sl/10 get_or_request_feature_effects_multiclass()[][] \T1/qtm/m/n/10
 meth-ods. For date-time mod-els use fol-low-

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\T1/qtm/m/n/10 ing meth-ods [][]\T1/txtt/m/sl/10 datarobot.models.DatetimeModel
.request_feature_effects_multiclass()[][]\T1/qtm/m/n/10 ,

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[][]\T1/txtt/m/sl/10 datarobot.models.DatetimeModel.get_feature_effects_multicl
ass()[][] \T1/qtm/m/n/10 or [][]\T1/txtt/m/sl/10 datarobot.models.
[938]
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[]\T1/qtm/m/n/10 fix [][]\T1/txtt/m/sl/10 datarobot.CustomTaskVersion[][] \T1/q
tm/m/n/10 and [][]\T1/txtt/m/sl/10 datarobot.CustomModelVersion[][] \T1/qtm/m/n
/10 to cor-rectly for-mat
[939]
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[]\T1/qtm/m/n/10 Added the abil-ity to re-quest a spe-cific model be pre-pared 
for de-ploy-ment us-ing [][]\T1/txtt/m/sl/10 Project.
[940] [941]
Underfull \hbox (badness 10000) in paragraph at lines 87109--87112
[]\T1/qtm/m/n/10 The \T1/txtt/m/n/10 required_metadata \T1/qtm/m/n/10 prop-erty
 of [][]\T1/txtt/m/sl/10 datarobot.CustomModelVersion[][] \T1/qtm/m/n/10 has be
en dep-re-cated.

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[]\T1/qtm/m/n/10 The \T1/txtt/m/n/10 required_metadata \T1/qtm/m/n/10 prop-erty
 of [][]\T1/txtt/m/sl/10 datarobot.CustomTaskVersion[][] \T1/qtm/m/n/10 has bee
n dep-re-cated.
[942]
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[]\T1/qtm/m/n/10 Sup-port for Batch Pre-dic-tion Job Def-i-ni-tions has now bee
n added through the fol-low-ing class:

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[]\T1/qtm/m/n/10 Added method to down-load fea-ture dis-cov-ery recipe SQLs (li
m-ited beta fea-ture). [][]\T1/txtt/m/sl/10 Project.
[943]
Underfull \hbox (badness 10000) in paragraph at lines 87403--87408
[]\T1/qtm/m/n/10 Par-tial his-tory pre-dic-tions can be made with time se-ries 
time se-ries mul-ti-series mod-els us-

Underfull \hbox (badness 10000) in paragraph at lines 87403--87408
\T1/qtm/m/n/10 ing the \T1/txtt/m/n/10 allow_partial_history_time_series_predic
tions \T1/qtm/m/n/10 at-tribute of the [][]\T1/txtt/m/sl/10 datarobot.

Underfull \hbox (badness 10000) in paragraph at lines 87428--87436
[][]\T1/txtt/m/sl/10 PairwiseJointProbabilities[][] \T1/qtm/m/n/10 and [][]\T1/
txtt/m/sl/10 PairwiseConditionalProbabilities[][] \T1/qtm/m/n/10 or [][]\T1/txt
t/m/sl/10 Feature.

Underfull \hbox (badness 10000) in paragraph at lines 87428--87436
\T1/txtt/m/sl/10 get_pairwise_correlations[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/s
l/10 Feature.get_pairwise_joint_probabilities[][] \T1/qtm/m/n/10 and [][]\T1/tx
tt/m/sl/10 Feature.
[944]
Underfull \hbox (badness 10000) in paragraph at lines 87499--87502
[]\T1/qtm/m/n/10 Sup-port for down-load-ing fea-ture dis-cov-ery train-ing or p
re-dic-tion dataset us-ing [][]\T1/txtt/m/sl/10 Project.

Underfull \hbox (badness 10000) in paragraph at lines 87504--87510
[]\T1/qtm/m/n/10 Added [][]\T1/txtt/m/sl/10 datarobot.models.FeatureAssociation
Matrix[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 datarobot.models.

Underfull \hbox (badness 10000) in paragraph at lines 87504--87510
\T1/txtt/m/sl/10 FeatureAssociationMatrixDetails[][] \T1/qtm/m/n/10 and [][]\T1
/txtt/m/sl/10 datarobot.models.FeatureAssociationFeaturelists[][]

Underfull \hbox (badness 7168) in paragraph at lines 87529--87532
[]\T1/qtm/m/n/10 Re-move \T1/qtm/m/it/10 de-sired_memory \T1/qtm/m/n/10 param f
rom the fol-low-ing classes: [][]\T1/txtt/m/sl/10 datarobot.CustomInferenceMode
l[][]\T1/qtm/m/n/10 ,

Underfull \hbox (badness 10000) in paragraph at lines 87534--87541
[]\T1/qtm/m/n/10 Re-move \T1/txtt/m/n/10 desired_memory \T1/qtm/m/n/10 param fr
om the fol-low-ing meth-ods: [][]\T1/txtt/m/sl/10 CustomInferenceModel.

Underfull \hbox (badness 10000) in paragraph at lines 87534--87541
\T1/txtt/m/sl/10 create[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 CustomModelVer
sion.create_clean[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 CustomModelVersion.c
reate_from_previous[][]\T1/qtm/m/n/10 ,
[945]
Underfull \hbox (badness 8170) in paragraph at lines 87665--87668
[]\T1/qtm/m/n/10 Fea-ture dis-cov-ery projects can now be cre-ated us-ing the [
][]\T1/txtt/m/sl/10 Project.start[][] \T1/qtm/m/n/10 method by pro-vid-ing
[946]
Underfull \hbox (badness 10000) in paragraph at lines 87753--87758
[]\T1/qtm/m/n/10 New \T1/txtt/m/n/10 sampling_method \T1/qtm/m/n/10 param in []
[]\T1/txtt/m/sl/10 Model.train_datetime[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/1
0 Project.train_datetime[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 87778--87780
[]\T1/qtm/m/n/10 Class \T1/txtt/m/n/10 FeatureEngineeringGraph \T1/qtm/m/n/10 h
as been re-moved. Use [][]\T1/txtt/m/sl/10 datarobot.models.
[947]
Underfull \hbox (badness 10000) in paragraph at lines 87900--87903
[]\T1/qtm/m/n/10 Added a new method to trig-ger Fea-ture Im-pact cal-cu-la-tion
 for a Cus-tom In-fer-ence Im-age:
[948] [949]
Underfull \hbox (badness 10000) in paragraph at lines 88043--88052
[]\T1/qtm/m/n/10 Added new ar-gu-ments \T1/txtt/m/n/10 explanation_algorithm \T
1/qtm/m/n/10 and \T1/txtt/m/n/10 max_explanations \T1/qtm/m/n/10 to method [][]
\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 88054--88061
[]\T1/qtm/m/n/10 Added new ar-gu-ments \T1/txtt/m/n/10 explanation_algorithm \T
1/qtm/m/n/10 and \T1/txtt/m/n/10 max_explanations \T1/qtm/m/n/10 to method [][]
\T1/txtt/m/sl/10 Model.
[950]
Underfull \hbox (badness 10000) in paragraph at lines 88254--88258
[]\T1/qtm/m/n/10 Batch Pre-dic-tion jobs now sup-port scor-ing to Azure and Goo
gle Cloud Stor-age with meth-ods
[951]
Underfull \hbox (badness 8132) in paragraph at lines 88292--88297
[]\T1/qtm/m/n/10 These meth-ods now pro-vide ad-di-tional meta-data fields in F
ea-ture Im-pact re-sults if called with

Underfull \hbox (badness 10000) in paragraph at lines 88312--88316
[]\T1/qtm/m/n/10 Sec-ondary dataset con-fig-u-ra-tion re-trieve and dele-tion i
s eas-ier now though new

Underfull \hbox (badness 10000) in paragraph at lines 88312--88316
[][]\T1/txtt/m/sl/10 SecondaryDatasetConfigurations.delete[][] \T1/qtm/m/n/10 s
oft deletes a Sec-ondary dataset con-fig-u-ra-tion.
[952] [953]
Underfull \hbox (badness 10000) in paragraph at lines 88582--88586
[]\T1/qtm/m/n/10 A new boolean at-tribute \T1/txtt/m/n/10 unsupervised_mode \T1
/qtm/m/n/10 was added to [][]\T1/txtt/m/sl/10 datarobot.
[954]
Underfull \hbox (badness 10000) in paragraph at lines 88650--88654
[]\T1/qtm/m/n/10 Time se-ries model de-ploy-ments now sup-port pre-dic-tion in-
ter-vals. See

Underfull \hbox (badness 10000) in paragraph at lines 88650--88654
[][]\T1/txtt/m/sl/10 Deployment.get_prediction_intervals_settings[][] \T1/qtm/m
/n/10 and [][]\T1/txtt/m/sl/10 Deployment.

Underfull \hbox (badness 10000) in paragraph at lines 88703--88706
[]\T1/qtm/m/n/10 It's now pos-si-ble to get fea-ture as-so-ci-a-tion sta-tuses 
for fea-turelists us-ing [][]\T1/txtt/m/sl/10 Project.

Underfull \hbox (badness 7925) in paragraph at lines 88740--88742
[]\T1/qtm/m/n/10 Method [][]\T1/txtt/m/sl/10 Project.set_target[][] \T1/qtm/m/n
/10 sup-port new op-tional pa-ram-e-ters \T1/txtt/m/n/10 featureEngineeringGrap
hs \T1/qtm/m/n/10 and

Underfull \hbox (badness 10000) in paragraph at lines 88748--88753
[]\T1/qtm/m/n/10 Se-ries ac-cu-racy re-trieval meth-ods ([][]\T1/txtt/m/sl/10 D
atetimeModel.get_series_accuracy_as_dataframe[][] \T1/qtm/m/n/10 and
[955] [956]
Underfull \hbox (badness 10000) in paragraph at lines 88830--88832
[]\T1/qtm/m/n/10 Mono-tonic con-straints are now sup-ported for OTV projects. T
o that end, the pa-ram-e-ters

Underfull \hbox (badness 10000) in paragraph at lines 88830--88832
\T1/txtt/m/n/10 monotonic_increasing_featurelist_id \T1/qtm/m/n/10 and \T1/txtt
/m/n/10 monotonic_decreasing_featurelist_id \T1/qtm/m/n/10 can be
[957] [958] [959]
Underfull \hbox (badness 10000) in paragraph at lines 89120--89129
[]\T1/qtm/m/n/10 Pre-vi-ously avail-able for only Eu-reqa mod-els, Ad-vanced Tu
n-ing meth-ods and ob-jects, in-clud-ing

Underfull \hbox (badness 10000) in paragraph at lines 89120--89129
[][]\T1/txtt/m/sl/10 Model.start_advanced_tuning_session[][]\T1/qtm/m/n/10 , []
[]\T1/txtt/m/sl/10 Model.get_advanced_tuning_parameters[][]\T1/qtm/m/n/10 , [][
]\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 89159--89161
[][][]\T1/txtt/m/sl/10 Project.upload_dataset[][] \T1/qtm/m/n/10 and [][]\T1/tx
tt/m/sl/10 Project.upload_dataset_from_data_source[][] \T1/qtm/m/n/10 will re-t
urn a
[960]
Underfull \hbox (badness 10000) in paragraph at lines 89281--89284
[]\T1/qtm/m/n/10 New class for work-ing with model com-pli-ance doc-u-men-ta-ti
on fea-ture of DataRobot: class

Underfull \hbox (badness 10000) in paragraph at lines 89300--89305
[]\T1/qtm/m/n/10 Cross se-ries fea-tures can now be cre-ated within time se-rie
s mul-ti-series projects us-ing

Underfull \hbox (badness 10000) in paragraph at lines 89300--89305
\T1/qtm/m/n/10 the \T1/txtt/m/n/10 use_cross_series_features \T1/qtm/m/n/10 and
 \T1/txtt/m/n/10 aggregation_type \T1/qtm/m/n/10 at-tributes of the [][]\T1/txt
t/m/sl/10 datarobot.
[961]
Underfull \hbox (badness 10000) in paragraph at lines 89331--89335
[]\T1/qtm/m/n/10 New \T1/txtt/m/n/10 number_of_known_in_advance_features \T1/qt
m/m/n/10 at-tribute has been added to the [][]\T1/txtt/m/sl/10 datarobot.

Underfull \hbox (badness 10000) in paragraph at lines 89362--89366
[]\T1/qtm/m/n/10 Train-ing pre-dic-tions for date-time par-ti-tioned projects n
ow sup-port the new data sub-set
[962]
Underfull \hbox (badness 10000) in paragraph at lines 89421--89429
[]\T1/qtm/m/n/10 New meth-ods and ob-jects, in-clud-ing [][]\T1/txtt/m/sl/10 Mo
del.start_advanced_tuning_session[][]\T1/qtm/m/n/10 , [][]\T1/txtt/m/sl/10 Mode
l.

Underfull \hbox (badness 7504) in paragraph at lines 89421--89429
\T1/txtt/m/sl/10 get_advanced_tuning_parameters[][]\T1/qtm/m/n/10 , [][]\T1/txt
t/m/sl/10 Model.advanced_tune[][]\T1/qtm/m/n/10 , and [][]\T1/txtt/m/sl/10 Adva
ncedTuningSession[][]\T1/qtm/m/n/10 , were

Underfull \hbox (badness 10000) in paragraph at lines 89444--89447
[]\T1/qtm/m/n/10 A cus-tom pre-dic-tion thresh-old may now be con-fig-ured for 
each model via [][]\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 89454--89456
[]\T1/qtm/m/n/10 In-di-vid-ual cross val-i-da-tion scores can be re-trieved for
 new mod-els us-ing [][]\T1/txtt/m/sl/10 Model.

Underfull \hbox (badness 10000) in paragraph at lines 89496--89500
[][][]\T1/txtt/m/sl/10 ModelRecommendation.get[][] \T1/qtm/m/n/10 now ac-cepts 
an op-tional pa-ram-e-ter of type \T1/txtt/m/n/10 datarobot.enums.
[963]
Underfull \hbox (badness 10000) in paragraph at lines 89613--89617
[]\T1/qtm/m/n/10 Added a new fea-ture to re-trieve fea-ture logs for time se-ri
es projects. Check [][]\T1/txtt/m/sl/10 datarobot.

Underfull \hbox (badness 10000) in paragraph at lines 89613--89617
\T1/txtt/m/sl/10 DatetimePartitioning.feature_log_list()[][] \T1/qtm/m/n/10 and
 [][]\T1/txtt/m/sl/10 datarobot.DatetimePartitioning.
[964] [965] [966] [967] [968] [969] [970] [971] [972] [973] [974] [975]
[976]
Underfull \hbox (badness 6016) in paragraph at lines 90807--90811
[]\T1/qtm/m/n/10 In sev-eral places where \T1/txtt/m/n/10 AppPlatformError \T1/
qtm/m/n/10 was be-ing raised, now \T1/txtt/m/n/10 TypeError\T1/qtm/m/n/10 , \T1
/txtt/m/n/10 ValueError \T1/qtm/m/n/10 or

Underfull \hbox (badness 10000) in paragraph at lines 90827--90832
[]\T1/qtm/m/n/10 If a \T1/txtt/m/n/10 ClientError \T1/qtm/m/n/10 or \T1/txtt/m/
n/10 ServerError \T1/qtm/m/n/10 oc-curs dur-ing a call to \T1/txtt/m/n/10 Proje
ct.from_async\T1/qtm/m/n/10 , then a
[977]
Underfull \hbox (badness 10000) in paragraph at lines 90898--90901
[]\T1/txtt/m/n/10 recommendation_settings \T1/qtm/m/n/10 pa-ram-e-ter of \T1/tx
tt/m/n/10 Project.start \T1/qtm/m/n/10 is dep-re-cated in fa-vor of
[978] [979] [980] [981] [982] (./datarobot-public-api-client.ind [983] [984]
[985]
Underfull \hbox (badness 5548) in paragraph at lines 103--105
[]\T1/txtt/m/n/10 bucket_sample_sizes \T1/qtm/m/n/10 (\T1/qtm/m/it/10 datarobot
.models.deployment.custom_metrics.CustomMetricValuesOverBatch prop-erty\T1/qtm/
m/n/10 ),

Underfull \hbox (badness 10000) in paragraph at lines 105--107
[]\T1/txtt/m/n/10 bucket_sample_sizes \T1/qtm/m/n/10 (\T1/qtm/m/it/10 datarobot
.models.deployment.custom_metrics.CustomMetricValuesOverTime prop-erty\T1/qtm/m
/n/10 ),
[986] [987] [988] [989] [990] [991]
Underfull \hbox (badness 10000) in paragraph at lines 658--660
[]\T1/txtt/m/n/10 find_anomalous_regions() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 data
robot.models.anomaly_assessment.AnomalyAssessmentPredictionsPreview
[992] [993] [994] [995] [996]
Underfull \hbox (badness 10000) in paragraph at lines 1041--1043
[]\T1/txtt/m/n/10 get_buckets_as_dataframe() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.deployment.custom_metrics.CustomMetricValuesOverBatch

Underfull \hbox (badness 10000) in paragraph at lines 1043--1045
[]\T1/txtt/m/n/10 get_buckets_as_dataframe() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.deployment.custom_metrics.CustomMetricValuesOverTime
[997]
Overfull \hbox (51.0944pt too wide) in paragraph at lines 1115--1117
[]\T1/txtt/m/n/10 get_document_page_with_text_locations() \T1/qtm/m/n/10 (\T1/q
tm/m/it/10 datarobot.models.documentai.document.DocumentTextExtractionSamplePag
e

Underfull \hbox (badness 10000) in paragraph at lines 1130--1132
[]\T1/txtt/m/n/10 get_explanations_data_in_regions() \T1/qtm/m/n/10 (\T1/qtm/m/
it/10 datarobot.models.anomaly_assessment.AnomalyAssessmentRecord
[998] [999] [1000] [1001] [1002]
Underfull \hbox (badness 10000) in paragraph at lines 1630--1632
[]\T1/txtt/m/n/10 is_model_compliance_initialized \T1/qtm/m/n/10 (\T1/qtm/m/it/
10 datarobot.models.automated_documentation.AutomatedDocument prop-
[1003] [1004]
Underfull \hbox (badness 10000) in paragraph at lines 1775--1777
[]\T1/txtt/m/n/10 list_available_document_types() \T1/qtm/m/n/10 (\T1/qtm/m/it/
10 datarobot.models.automated_documentation.AutomatedDocument class
[1005] [1006] [1007] [1008] [1009] [1010] [1011] [1012]
Underfull \hbox (badness 7722) in paragraph at lines 2494--2496
[]\T1/txtt/m/n/10 validate_task_parameters() \T1/qtm/m/n/10 (\T1/qtm/m/it/10 da
tarobot.models.user_blueprints.models.UserBlueprintValidateTaskParameters
[1013]) [1014] (./datarobot-public-api-client.aux)

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