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Implementing machine learning models to predict which customers are likely to cancel a subscription to a service based on how they use the service.

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Customer-Churn-Prediction

The purpose of this research is to develop and design an effective and efficient model for customer churn prediction in telecommunication industry

Data Preparation Steps

Data Conversion
Sparseness Elimination
Outliers Detection
Features selection
Data Encoding
Data Standardization

Implemented Models

Gradient Boost
KNN
xgBoost
Decision Tree
AdaBoost
Random Forest
Logistic Regression
Gaussian NB
SVM

Evaluation

Trains and test scores
Accuracy
Classification Report
Confusion Matrix
Area under curve

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Implementing machine learning models to predict which customers are likely to cancel a subscription to a service based on how they use the service.

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