This code aims at getting the best model and calculating AUC-ROC and F1-Score on imbalanced classification problem
Beta Bank customers are leaving: little by little, chipping away every month. The bankers figured out it’s cheaper to save the existing customers rather than to attract new ones. We need to predict whether a customer will leave the bank soon. You have the data on clients’ past behavior and termination of contracts with the bank. Build a model with the maximum possible F1 score. To pass the project, you need an F1 score of at least 0.59. Check the F1 for the test set.
Build a model with the maximum possible F1 score that can predict whether a customer will churn or not
Dataset URL (CSV File): https://bit.ly/2XZK7Bo
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent