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%global _empty_manifest_terminate_build 0
Name: python-erroranalysis
Version: 0.4.2
Release: 1
Summary: Core error analysis APIs
License: MIT License
URL: https://github.com/microsoft/responsible-ai-widgets
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/7c/49/21fe58730caef0298df5e3cef0dea5c6d22ac9d73ac993141c340f3f2405/erroranalysis-0.4.2.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-scipy
Requires: python3-scikit-learn
Requires: python3-lightgbm
Requires: python3-raiutils
%description
# Error Analysis SDK for Python
### This package has been tested with Python 3.6, 3.7, 3.8 and 3.9
The error analysis sdk enables users to get a deeper understanding of machine learning model errors. When evaluating a machine learning model, aggregate accuracy is not sufficient and single-score evaluation may hide important conditions of inaccuracies. Use Error Analysis to identify cohorts with higher error rates and diagnose the root causes behind these errors.
Highlights of the package include:
- The error heatmap to investigate how one or two input features impact the error rate across cohorts
- The decision tree surrogate model trained on errors to discover cohorts with high error rates across multiple features. Investigate indicators such as error rate, error coverage, and data representation for each discovered cohort.
Please see the main documentation website:
https://erroranalysis.ai/
Auto-generated sphinx API documentation can be found here:
https://erroranalysis.ai/raiwidgets.html
The open source code can be found here:
https://github.com/microsoft/responsible-ai-widgets
%package -n python3-erroranalysis
Summary: Core error analysis APIs
Provides: python-erroranalysis
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-erroranalysis
# Error Analysis SDK for Python
### This package has been tested with Python 3.6, 3.7, 3.8 and 3.9
The error analysis sdk enables users to get a deeper understanding of machine learning model errors. When evaluating a machine learning model, aggregate accuracy is not sufficient and single-score evaluation may hide important conditions of inaccuracies. Use Error Analysis to identify cohorts with higher error rates and diagnose the root causes behind these errors.
Highlights of the package include:
- The error heatmap to investigate how one or two input features impact the error rate across cohorts
- The decision tree surrogate model trained on errors to discover cohorts with high error rates across multiple features. Investigate indicators such as error rate, error coverage, and data representation for each discovered cohort.
Please see the main documentation website:
https://erroranalysis.ai/
Auto-generated sphinx API documentation can be found here:
https://erroranalysis.ai/raiwidgets.html
The open source code can be found here:
https://github.com/microsoft/responsible-ai-widgets
%package help
Summary: Development documents and examples for erroranalysis
Provides: python3-erroranalysis-doc
%description help
# Error Analysis SDK for Python
### This package has been tested with Python 3.6, 3.7, 3.8 and 3.9
The error analysis sdk enables users to get a deeper understanding of machine learning model errors. When evaluating a machine learning model, aggregate accuracy is not sufficient and single-score evaluation may hide important conditions of inaccuracies. Use Error Analysis to identify cohorts with higher error rates and diagnose the root causes behind these errors.
Highlights of the package include:
- The error heatmap to investigate how one or two input features impact the error rate across cohorts
- The decision tree surrogate model trained on errors to discover cohorts with high error rates across multiple features. Investigate indicators such as error rate, error coverage, and data representation for each discovered cohort.
Please see the main documentation website:
https://erroranalysis.ai/
Auto-generated sphinx API documentation can be found here:
https://erroranalysis.ai/raiwidgets.html
The open source code can be found here:
https://github.com/microsoft/responsible-ai-widgets
%prep
%autosetup -n erroranalysis-0.4.2
%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-erroranalysis -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.2-1
- Package Spec generated
|
