Provide insights on bank customer data and and build model for predicting the future possibility of customers leaving the bank
data set link ->http://superdatascience.com/training/ data file name ->Churn_Modelling.csv
Input features RowNumber CustomerId Surname CreditScore Geography Gender Age Tenure Balance NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited
Aim ->provide insights to determine the reason for customers to exit the bank methods-> Data analysis using TABLEAU, Data modeling using R, Matlab
File names Visualization.docx contains the graphical visualization analysis. the training data file is converted from .xlsx to csv
Modelling contains the model for predicting the future possibility of customers leaving the bank Two methods are explained one below the other with confusion matrix with 1 or 0 for exit or not exit method 1 - Random forest with k-fold Validation method 2 - Logistic regression with normal Validation