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Up the version to 0.14 (#632)
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docs/changelog.rst

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Changelog
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=========
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0.14.0 (July 2023)
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-----------------
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- CausalML surpassed `2MM downloads <https://pepy.tech/project/causalml>`_ on PyPI and `4,100 stars <https://github.com/uber/causalml/stargazers>`_ on GitHub. Thanks for choosing CausalML and supporting us on GitHub.
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- We have 7 new contributors: @darthtrevino, @ras44, @AbhishekVermaDH, @joel-mcmurry, @AlxClt, @kklein, and @volico. Thanks for your contributions!
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Updates
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~~~~~~~~~~~~~
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- Fix the readthedocs build failure by @jeongyoonlee in https://github.com/uber/causalml/pull/545
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- Add pyproject.toml with basic build dependencies for PEP518 compliance by @darthtrevino in https://github.com/uber/causalml/pull/553
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- bump numpy from 1.20.3 to 1.23.2 in environment-py38.yml #338 by @ras44 in https://github.com/uber/causalml/pull/550
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- CausalTree split criterions fix and fit optimization by @alexander-pv in https://github.com/uber/causalml/pull/557
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- fixing math notations for proper rendering by @AbhishekVermaDH in https://github.com/uber/causalml/pull/558
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- Update methodology.rst by @joel-mcmurry in https://github.com/uber/causalml/pull/568
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- Causal trees bootstrapping and `max_leaf_nodes` fixes with minor update by @alexander-pv in https://github.com/uber/causalml/pull/583
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- Fix #596 by @AlxClt in https://github.com/uber/causalml/pull/597
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- Add **kwargs to Explainer.plot_shap_values() by @jeongyoonlee in https://github.com/uber/causalml/pull/603
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- Make the Adam optimization optional and learning rate/epochs configurable in DragonNet by @jeongyoonlee in https://github.com/uber/causalml/pull/604
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- Fix bug in variance calculation in drivlearner. by @huigangchen in https://github.com/uber/causalml/pull/606
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- Bug Fix in Dragonnet: Adam parameter name lr depreciation by @huigangchen in https://github.com/uber/causalml/pull/617
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- Fix AttributeError in builds with numpy>=1.24 and pandas>=2.0 by @jeongyoonlee in https://github.com/uber/causalml/pull/631
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- Pass on **kwargs in `plot_shap_values` of base meta leaner by @kklein in https://github.com/uber/causalml/pull/627
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- Bump scipy from 1.4.1 to 1.10.0 by @dependabot in https://github.com/uber/causalml/pull/629
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- Feature/ttest criterion by @volico in https://github.com/uber/causalml/pull/570
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- Added Interaction Tree (IT), Causal Inference Tree (CIT), and Invariant DDP (IDDP) by @jroessler in https://github.com/uber/causalml/pull/562
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- Causal trees option to return counterfactual outcomes by @alexander-pv in https://github.com/uber/causalml/pull/623
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New contributors
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~~~~~~~~~~~~~~~~
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- @darthtrevino made their first contribution in https://github.com/uber/causalml/pull/553
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- @ras44 made their first contribution in https://github.com/uber/causalml/pull/550
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- @AbhishekVermaDH made their first contribution in https://github.com/uber/causalml/pull/558
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- @joel-mcmurry made their first contribution in https://github.com/uber/causalml/pull/568
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- @AlxClt made their first contribution in https://github.com/uber/causalml/pull/597
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- @kklein made their first contribution in https://github.com/uber/causalml/pull/627
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- @volico made their first contribution in https://github.com/uber/causalml/pull/570
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0.13.0 (Sep 2022)
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- CausalML surpassed `1MM downloads <https://pepy.tech/project/causalml>`_ on PyPI and `3,200 stars <https://github.com/uber/causalml/stargazers>`_ on GitHub. Thanks for choosing CausalML and supporting us on GitHub.

docs/conf.py

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# General information about the project.
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project = "causalml"
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copyright = "2019 Uber Technologies, Inc."
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copyright = "2023 Uber Technologies, Inc."
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author = "CausalML"
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# The version info for the project you're documenting, acts as replacement
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# for |version| and |release|, also used in various other places throughout
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# the built documents.
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#
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# The short X.Y version.
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version = causalml.__version__
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import importlib.metadata
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version = importlib.metadata.version("causalml")
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# The full version, including alpha/beta/rc tags.
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# release = causalml.__version__
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pyproject.toml

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[project]
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name = "causalml"
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version = "0.13.0"
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version = "0.14.0"
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description = "Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms"
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readme = { file = "README.md", content-type = "text/markdown" }
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