# 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
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### **Function:**
get_performance_metrics Function that returns evaluation metrics
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### **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
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### **Function:**
top_decile_lift Function that returns top decile lift of a sample
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### **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
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### **Function:**
lift_curve Function that plots lift curve of a model
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### **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
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### **Function:**
gain_curve Function that plots gain curve of a model
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### **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
