Artificial Neural Network (ChurnModeling)

ANN regression model

ANN Regressor and Classifier Churn Modelling Dataset

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Churn Modeling using Artificial Neural Network ( ANN ) with keras library in Python, & h2o library in R.

A machine learning project implemented in R to predict customer churn using an Artificial Neural Network (ANN). The model analyzes customer behavior and service-related features to identify the likelihood of churn, helping businesses improve customer retention strategies.

Churn Prediction in Telecoms Industry Using R Telecommunication market is expanding day by day. Companies are facing a severe loss of revenue due to increasing competition hence the loss of customers. They are trying to find the reasons of losing customers by measuring customer loyalty to regain the lost customers. The customers leaving the current company and moving to another telecom company are called churn. This Analysis will use ANN and SVM models to find the best model for the study.

Advanced data mining project on classifying customer churn by using machine learning algorithms such as random forest, C5.0, Decision tree, KNN, ANN, and SVM. CRISP-DM approach was followed for developing the project. Accuracy rate, Error rate, Precision, Recall, F1 and ROC curve was generated using R programming and the efficient model was found comparing these values.