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diff --git a/python-churneval.spec b/python-churneval.spec new file mode 100644 index 0000000..63a682b --- /dev/null +++ b/python-churneval.spec @@ -0,0 +1,469 @@ +%global _empty_manifest_terminate_build 0 +Name: python-churneval +Version: 1.3 +Release: 1 +Summary: churneval is a python package for evaluating churn models +License: LICENSE.txt +URL: https://pypi.org/project/churneval/ +Source0: https://mirrors.aliyun.com/pypi/web/packages/0d/b7/3df790382621d9510eb905cb0e6625913e94a027a08a33b9b1cfa7d0c135/churneval-1.3.tar.gz +BuildArch: noarch + +Requires: python3-churneval +Requires: python3-pandas +Requires: python3-sklearn +Requires: python3-matplotlib + +%description +# Package "churneval" + +#### **Version:** 1.3 + +#### **Author:** *Soumi De* + +#### **Maintained by:** Soumi De <<soumi.de@res.christuniversity.in>> + +#### **Description:** +churneval is a package to evaluate models used in churn classification. The evaluation metrics include accuracy, sensitivity, specificity, precision, F1-score and top decile lift. The package also contains functions to plot lift curve and gain curve of a model. + +#### **License:** GPL-3 + +#### **Date:** 12th November, 2021 +<br> + +___ + + +### **Function:** + get_performance_metrics Function that returns evaluation metrics + +___ +<br> + +### **Usage:** + +from churneval import get_performance_metrics + +get_performance_metrics(model_name, true_class, predicted_class, predicted_probs) + +### **Arguments:** +* model_name: Abbreviated name of the churn model (in text) +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_class: An array of binary predicted class with shape (n,) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +A dataframe consisting of elements given below: +* Model_Name: Abbreviated name of the churn model +* Accuracy: Accuracy of churn model +* Confusion Matrix: A 2X2 array representing confusion matrix +* Precision: Precision value +* Sensitivity: Sensitivity value +* Specificity: Specificity value +* F1-score: F1-score +* ROC_score: Area under the curve +* top_dec_lift: Top decile lift value + +<br> + + +___ + +### **Function:** + top_decile_lift Function that returns top decile lift of a sample + +___ +<br> + +### **Usage:** + +from churneval import top_decile_lift + +top_decile_lift(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A float object with top decile lift value + +<br> + + +___ + +### **Function:** + lift_curve Function that plots lift curve of a model + +___ +<br> + +### **Usage:** + +from churneval import lift_curve + +lift_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Lift of the model + +<br> + + +___ + +### **Function:** + gain_curve Function that plots gain curve of a model + +___ +<br> + +### **Usage:** + +from churneval import gain_curve + +gain_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Gain of the model + + + + + +%package -n python3-churneval +Summary: churneval is a python package for evaluating churn models +Provides: python-churneval +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-churneval +# Package "churneval" + +#### **Version:** 1.3 + +#### **Author:** *Soumi De* + +#### **Maintained by:** Soumi De <<soumi.de@res.christuniversity.in>> + +#### **Description:** +churneval is a package to evaluate models used in churn classification. The evaluation metrics include accuracy, sensitivity, specificity, precision, F1-score and top decile lift. The package also contains functions to plot lift curve and gain curve of a model. + +#### **License:** GPL-3 + +#### **Date:** 12th November, 2021 +<br> + +___ + + +### **Function:** + get_performance_metrics Function that returns evaluation metrics + +___ +<br> + +### **Usage:** + +from churneval import get_performance_metrics + +get_performance_metrics(model_name, true_class, predicted_class, predicted_probs) + +### **Arguments:** +* model_name: Abbreviated name of the churn model (in text) +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_class: An array of binary predicted class with shape (n,) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +A dataframe consisting of elements given below: +* Model_Name: Abbreviated name of the churn model +* Accuracy: Accuracy of churn model +* Confusion Matrix: A 2X2 array representing confusion matrix +* Precision: Precision value +* Sensitivity: Sensitivity value +* Specificity: Specificity value +* F1-score: F1-score +* ROC_score: Area under the curve +* top_dec_lift: Top decile lift value + +<br> + + +___ + +### **Function:** + top_decile_lift Function that returns top decile lift of a sample + +___ +<br> + +### **Usage:** + +from churneval import top_decile_lift + +top_decile_lift(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A float object with top decile lift value + +<br> + + +___ + +### **Function:** + lift_curve Function that plots lift curve of a model + +___ +<br> + +### **Usage:** + +from churneval import lift_curve + +lift_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Lift of the model + +<br> + + +___ + +### **Function:** + gain_curve Function that plots gain curve of a model + +___ +<br> + +### **Usage:** + +from churneval import gain_curve + +gain_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Gain of the model + + + + + +%package help +Summary: Development documents and examples for churneval +Provides: python3-churneval-doc +%description help +# Package "churneval" + +#### **Version:** 1.3 + +#### **Author:** *Soumi De* + +#### **Maintained by:** Soumi De <<soumi.de@res.christuniversity.in>> + +#### **Description:** +churneval is a package to evaluate models used in churn classification. The evaluation metrics include accuracy, sensitivity, specificity, precision, F1-score and top decile lift. The package also contains functions to plot lift curve and gain curve of a model. + +#### **License:** GPL-3 + +#### **Date:** 12th November, 2021 +<br> + +___ + + +### **Function:** + get_performance_metrics Function that returns evaluation metrics + +___ +<br> + +### **Usage:** + +from churneval import get_performance_metrics + +get_performance_metrics(model_name, true_class, predicted_class, predicted_probs) + +### **Arguments:** +* model_name: Abbreviated name of the churn model (in text) +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_class: An array of binary predicted class with shape (n,) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +A dataframe consisting of elements given below: +* Model_Name: Abbreviated name of the churn model +* Accuracy: Accuracy of churn model +* Confusion Matrix: A 2X2 array representing confusion matrix +* Precision: Precision value +* Sensitivity: Sensitivity value +* Specificity: Specificity value +* F1-score: F1-score +* ROC_score: Area under the curve +* top_dec_lift: Top decile lift value + +<br> + + +___ + +### **Function:** + top_decile_lift Function that returns top decile lift of a sample + +___ +<br> + +### **Usage:** + +from churneval import top_decile_lift + +top_decile_lift(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A float object with top decile lift value + +<br> + + +___ + +### **Function:** + lift_curve Function that plots lift curve of a model + +___ +<br> + +### **Usage:** + +from churneval import lift_curve + +lift_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Lift of the model + +<br> + + +___ + +### **Function:** + gain_curve Function that plots gain curve of a model + +___ +<br> + +### **Usage:** + +from churneval import gain_curve + +gain_curve(true_class, predicted_probs) + +### **Arguments:** +* true_class: A dataframe of true class labels with shape (n,1) +* predicted_probs: An array of predicted class probabilities with shape (n,) + +### **Returned Values:** + +* A plot that shows lift curve + * x-axis: Proportion of data + * y-axis: Gain of the model + + + + + +%prep +%autosetup -n churneval-1.3 + +%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-churneval -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3-1 +- Package Spec generated |