Employee Attrition Machine Learning Project
This project focusing on using machine learning models to predict the employees behavior of resignation.
After tying methods including logistic regression, Support Vector Machine, Random Forest, and Additive Boost, the final models for this project is Additive Boosting Model with Decision Tree as the base estimator.
The final model achieve an accuracy ove 95% on the testing set, and consdier the data set is extremely imbalanced, the model also has great performance including 0.95 F1 Score.
Packages/Libraries: : numpy, pandas, seaborn, sklearn
Methods/Models: : Logistic Regression with L1 penalty, Additive Boosting with Decision Tree.