%global _empty_manifest_terminate_build 0 Name: python-probatus Version: 2.0.0 Release: 1 Summary: Validation of binary classifiers and data used to develop them License: MIT License URL: https://github.com/ing-bank/probatus Source0: https://mirrors.aliyun.com/pypi/web/packages/7a/7f/42a29bc5a2615232bac9e10a2ff13760724bc1736be1ed635572b158f51c/probatus-2.0.0.tar.gz BuildArch: noarch Requires: python3-scikit-learn Requires: python3-pandas Requires: python3-matplotlib Requires: python3-scipy Requires: python3-joblib Requires: python3-tqdm Requires: python3-shap Requires: python3-numpy Requires: python3-numba Requires: python3-scikit-learn Requires: python3-pandas Requires: python3-matplotlib Requires: python3-scipy Requires: python3-joblib Requires: python3-tqdm Requires: python3-shap Requires: python3-numpy Requires: python3-numba Requires: python3-lightgbm Requires: python3-catboost Requires: python3-xgboost Requires: python3-flake8 Requires: python3-black Requires: python3-pre-commit Requires: python3-mypy Requires: python3-flake8-docstrings Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-pyflakes Requires: python3-seaborn Requires: python3-jupyter Requires: python3-tabulate Requires: python3-nbconvert Requires: python3-pre-commit Requires: python3-isort Requires: python3-codespell Requires: python3-mkdocs-material Requires: python3-mkdocs-git-revision-date-localized-plugin Requires: python3-mkdocs-git-authors-plugin Requires: python3-mkdocs-table-reader-plugin Requires: python3-mkdocs-enumerate-headings-plugin Requires: python3-mkdocs-awesome-pages-plugin Requires: python3-mkdocs-minify-plugin Requires: python3-mknotebooks Requires: python3-mkdocstrings Requires: python3-mkdocs-print-site-plugin Requires: python3-mkdocs-markdownextradata-plugin Requires: python3-scikit-learn Requires: python3-pandas Requires: python3-matplotlib Requires: python3-scipy Requires: python3-joblib Requires: python3-tqdm Requires: python3-shap Requires: python3-numpy Requires: python3-numba Requires: python3-lightgbm Requires: python3-catboost Requires: python3-xgboost %description [![pytest](https://github.com/ing-bank/probatus/workflows/Development/badge.svg)](https://github.com/ing-bank/probatus/actions?query=workflow%3A%22Development%22) [![PyPi Version](https://img.shields.io/pypi/pyversions/probatus)](#) [![PyPI](https://img.shields.io/pypi/v/probatus)](#) [![PyPI - Downloads](https://img.shields.io/pypi/dm/probatus)](#) ![GitHub contributors](https://img.shields.io/github/contributors/ing-bank/probatus) # Probatus ## Overview **Probatus** is a python package that helps validate binary classification models and the data used to develop them. Main features: - [probatus.interpret](https://ing-bank.github.io/probatus/api/model_interpret.html) provides shap-based model interpretation tools - [probatus.metric_volatility](https://ing-bank.github.io/probatus/api/metric_volatility.html) provides tools using bootstrapping and/or different random seeds to assess metric volatility/stability. - [probatus.sample_similarity](https://ing-bank.github.io/probatus/api/sample_similarity.html) to compare two datasets using resemblance modelling, f.e. `train` with out-of-time `test`. - [probatus.feature_elimination.ShapRFECV](https://ing-bank.github.io/probatus/api/feature_elimination.html) provides cross-validated Recursive Feature Elimination using shap feature importance. - [probatus.missing_values](https://ing-bank.github.io/probatus/api/imputation_selector.html) compares performance gains of different missing values imputation strategies for a given model. ## Installation ```bash pip install probatus ``` ## Documentation Documentation at [ing-bank.github.io/probatus/](https://ing-bank.github.io/probatus/). You can also check out blog posts about Probatus: - [Open-sourcing ShapRFECV — Improved feature selection powered by SHAP.](https://medium.com/ing-blog/open-sourcing-shaprfecv-improved-feature-selection-powered-by-shap-994fe7861560) - [Model Explainability — How to choose the right tool?](https://medium.com/ing-blog/model-explainability-how-to-choose-the-right-tool-6c5eabd1a46a) ## Contributing To learn more about making a contribution to Probatus, please see [`CONTRIBUTING.md`](CONTRIBUTING.md). %package -n python3-probatus Summary: Validation of binary classifiers and data used to develop them Provides: python-probatus BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-probatus [![pytest](https://github.com/ing-bank/probatus/workflows/Development/badge.svg)](https://github.com/ing-bank/probatus/actions?query=workflow%3A%22Development%22) [![PyPi Version](https://img.shields.io/pypi/pyversions/probatus)](#) [![PyPI](https://img.shields.io/pypi/v/probatus)](#) [![PyPI - Downloads](https://img.shields.io/pypi/dm/probatus)](#) ![GitHub contributors](https://img.shields.io/github/contributors/ing-bank/probatus) # Probatus ## Overview **Probatus** is a python package that helps validate binary classification models and the data used to develop them. Main features: - [probatus.interpret](https://ing-bank.github.io/probatus/api/model_interpret.html) provides shap-based model interpretation tools - [probatus.metric_volatility](https://ing-bank.github.io/probatus/api/metric_volatility.html) provides tools using bootstrapping and/or different random seeds to assess metric volatility/stability. - [probatus.sample_similarity](https://ing-bank.github.io/probatus/api/sample_similarity.html) to compare two datasets using resemblance modelling, f.e. `train` with out-of-time `test`. - [probatus.feature_elimination.ShapRFECV](https://ing-bank.github.io/probatus/api/feature_elimination.html) provides cross-validated Recursive Feature Elimination using shap feature importance. - [probatus.missing_values](https://ing-bank.github.io/probatus/api/imputation_selector.html) compares performance gains of different missing values imputation strategies for a given model. ## Installation ```bash pip install probatus ``` ## Documentation Documentation at [ing-bank.github.io/probatus/](https://ing-bank.github.io/probatus/). You can also check out blog posts about Probatus: - [Open-sourcing ShapRFECV — Improved feature selection powered by SHAP.](https://medium.com/ing-blog/open-sourcing-shaprfecv-improved-feature-selection-powered-by-shap-994fe7861560) - [Model Explainability — How to choose the right tool?](https://medium.com/ing-blog/model-explainability-how-to-choose-the-right-tool-6c5eabd1a46a) ## Contributing To learn more about making a contribution to Probatus, please see [`CONTRIBUTING.md`](CONTRIBUTING.md). %package help Summary: Development documents and examples for probatus Provides: python3-probatus-doc %description help [![pytest](https://github.com/ing-bank/probatus/workflows/Development/badge.svg)](https://github.com/ing-bank/probatus/actions?query=workflow%3A%22Development%22) [![PyPi Version](https://img.shields.io/pypi/pyversions/probatus)](#) [![PyPI](https://img.shields.io/pypi/v/probatus)](#) [![PyPI - Downloads](https://img.shields.io/pypi/dm/probatus)](#) ![GitHub contributors](https://img.shields.io/github/contributors/ing-bank/probatus) # Probatus ## Overview **Probatus** is a python package that helps validate binary classification models and the data used to develop them. Main features: - [probatus.interpret](https://ing-bank.github.io/probatus/api/model_interpret.html) provides shap-based model interpretation tools - [probatus.metric_volatility](https://ing-bank.github.io/probatus/api/metric_volatility.html) provides tools using bootstrapping and/or different random seeds to assess metric volatility/stability. - [probatus.sample_similarity](https://ing-bank.github.io/probatus/api/sample_similarity.html) to compare two datasets using resemblance modelling, f.e. `train` with out-of-time `test`. - [probatus.feature_elimination.ShapRFECV](https://ing-bank.github.io/probatus/api/feature_elimination.html) provides cross-validated Recursive Feature Elimination using shap feature importance. - [probatus.missing_values](https://ing-bank.github.io/probatus/api/imputation_selector.html) compares performance gains of different missing values imputation strategies for a given model. ## Installation ```bash pip install probatus ``` ## Documentation Documentation at [ing-bank.github.io/probatus/](https://ing-bank.github.io/probatus/). You can also check out blog posts about Probatus: - [Open-sourcing ShapRFECV — Improved feature selection powered by SHAP.](https://medium.com/ing-blog/open-sourcing-shaprfecv-improved-feature-selection-powered-by-shap-994fe7861560) - [Model Explainability — How to choose the right tool?](https://medium.com/ing-blog/model-explainability-how-to-choose-the-right-tool-6c5eabd1a46a) ## Contributing To learn more about making a contribution to Probatus, please see [`CONTRIBUTING.md`](CONTRIBUTING.md). %prep %autosetup -n probatus-2.0.0 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-probatus -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri Jun 09 2023 Python_Bot - 2.0.0-1 - Package Spec generated