NTI-Final-Assignment

NTI-Final-Assignment Use flask(python) and shiny dashboard (R) to build simple user interface to see how choosing classification model may affect prediction accuracy, using Customer Churn Dataset.

I tried to handle imbalanced classes in dataset using OverSampling technique (SMOTE Algorithm, RandomOverSampler) from imbalanced-learn API

Customer Churn probability (Yes / No).

i have used:

• Logistic Regression.
• KNN.
• SVM.
• Random forest.
• Decision Tree.
• Naive Bayes.