automatic import of python-mllytics

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diff --git a/.gitignore b/.gitignore
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+/MLLytics-0.2.2.tar.gz
diff --git a/python-mllytics.spec b/python-mllytics.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-MLLytics
+Version:	0.2.2
+Release:	1
+Summary:	A library of tools for easier evaluation of ML models.
+License:	MIT
+URL:		https://github.com/scottclay/MLLytics
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/5f/f2/5a26529eb02ab005060644781f7f6b28717cc1f16e5c62cbe3a95bfd0fbc/MLLytics-0.2.2.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-matplotlib
+Requires:	python3-seaborn
+Requires:	python3-pandas
+Requires:	python3-scikit-learn
+
+%description
+[![Upload Python Package](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml/badge.svg)](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml)
+
+# MLLytics
+
+## Installation instructions
+```pip install MLLytics```
+or
+```python setup.py install```
+or
+``` conda env create -f environment.yml```
+
+## Future
+### Improvements and cleanup
+* Comment all functions and classes
+* Add type hinting to all functions and classes (https://mypy.readthedocs.io/en/latest/cheat_sheet_py3.html)
+* Scoring functions
+* More output stats in overviews
+* Update reliability plot https://machinelearningmastery.com/calibrated-classification-model-in-scikit-learn/
+* Tests
+* Switch from my metrics to sklearn metrics where it makes sense? aka
+```fpr, tpr, thresholds = roc_curve(y[test], probas_[:, 1])```
+and more general macro/micro average metrics from: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html#sklearn.metrics.recall_score
+* Additional metrics (sensitivity, specificity, precision, negative predictive value, FPR, FNR,
+false discovery rate, accuracy, F1 score
+
+### Cosmetic
+* Fix size of confusion matrix
+* Check works with matplotlib 3
+* Tidy up legends and annotation text on plots
+* Joy plots
+* Brier score for calibration plot
+* Tidy up cross validation and plots (also repeated cross-validation)
+* Acc-thresholds graph
+
+### Recently completed
+* ~Allow figure size and font sizes to be passed into plotting functions~
+* ~Example guides for each function in jupyter notebooks~
+* ~MultiClassMetrics class to inherit from ClassMetrics and share common functions~
+* ~REGRESSION~
+
+## Contributing Authors
+* Scott Clay
+* David Sullivan
+
+
+
+
+%package -n python3-MLLytics
+Summary:	A library of tools for easier evaluation of ML models.
+Provides:	python-MLLytics
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-MLLytics
+[![Upload Python Package](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml/badge.svg)](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml)
+
+# MLLytics
+
+## Installation instructions
+```pip install MLLytics```
+or
+```python setup.py install```
+or
+``` conda env create -f environment.yml```
+
+## Future
+### Improvements and cleanup
+* Comment all functions and classes
+* Add type hinting to all functions and classes (https://mypy.readthedocs.io/en/latest/cheat_sheet_py3.html)
+* Scoring functions
+* More output stats in overviews
+* Update reliability plot https://machinelearningmastery.com/calibrated-classification-model-in-scikit-learn/
+* Tests
+* Switch from my metrics to sklearn metrics where it makes sense? aka
+```fpr, tpr, thresholds = roc_curve(y[test], probas_[:, 1])```
+and more general macro/micro average metrics from: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html#sklearn.metrics.recall_score
+* Additional metrics (sensitivity, specificity, precision, negative predictive value, FPR, FNR,
+false discovery rate, accuracy, F1 score
+
+### Cosmetic
+* Fix size of confusion matrix
+* Check works with matplotlib 3
+* Tidy up legends and annotation text on plots
+* Joy plots
+* Brier score for calibration plot
+* Tidy up cross validation and plots (also repeated cross-validation)
+* Acc-thresholds graph
+
+### Recently completed
+* ~Allow figure size and font sizes to be passed into plotting functions~
+* ~Example guides for each function in jupyter notebooks~
+* ~MultiClassMetrics class to inherit from ClassMetrics and share common functions~
+* ~REGRESSION~
+
+## Contributing Authors
+* Scott Clay
+* David Sullivan
+
+
+
+
+%package help
+Summary:	Development documents and examples for MLLytics
+Provides:	python3-MLLytics-doc
+%description help
+[![Upload Python Package](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml/badge.svg)](https://github.com/scottclay/MLLytics/actions/workflows/python-publish.yml)
+
+# MLLytics
+
+## Installation instructions
+```pip install MLLytics```
+or
+```python setup.py install```
+or
+``` conda env create -f environment.yml```
+
+## Future
+### Improvements and cleanup
+* Comment all functions and classes
+* Add type hinting to all functions and classes (https://mypy.readthedocs.io/en/latest/cheat_sheet_py3.html)
+* Scoring functions
+* More output stats in overviews
+* Update reliability plot https://machinelearningmastery.com/calibrated-classification-model-in-scikit-learn/
+* Tests
+* Switch from my metrics to sklearn metrics where it makes sense? aka
+```fpr, tpr, thresholds = roc_curve(y[test], probas_[:, 1])```
+and more general macro/micro average metrics from: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html#sklearn.metrics.recall_score
+* Additional metrics (sensitivity, specificity, precision, negative predictive value, FPR, FNR,
+false discovery rate, accuracy, F1 score
+
+### Cosmetic
+* Fix size of confusion matrix
+* Check works with matplotlib 3
+* Tidy up legends and annotation text on plots
+* Joy plots
+* Brier score for calibration plot
+* Tidy up cross validation and plots (also repeated cross-validation)
+* Acc-thresholds graph
+
+### Recently completed
+* ~Allow figure size and font sizes to be passed into plotting functions~
+* ~Example guides for each function in jupyter notebooks~
+* ~MultiClassMetrics class to inherit from ClassMetrics and share common functions~
+* ~REGRESSION~
+
+## Contributing Authors
+* Scott Clay
+* David Sullivan
+
+
+
+
+%prep
+%autosetup -n MLLytics-0.2.2
+
+%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-MLLytics -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.2-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+a5fb264b2e97dbb7c38967581ce1b8af  MLLytics-0.2.2.tar.gz