/* Date :: 02/08/2018 Author:: Raj Mehrotra */

IBM-HR-Analytics-Employee-Attrition-Performance dataset from the Kaggle.

I have first performed Exploratory Data Analysis on the data using various libraries like pandas,seaborn,matplotlib etc..

Then I have also used feature selection techniques like RFE (a wrapper method )to select the features. The data is then oversampled using the SMOTE (Synthetic MInority Oversampling Techniques) technique in order to deal with the imbalanced classes. Also the data is then scaled for better performance.

Lastly I have trained many ML models from the scikit-learn library for predictive modelling and compared the performance using Precision, Recall and other metrics .