Data Mining: Employee Churn Predictive Analysis

Utilized RStudio to build and test various machine learning models on a Kaggle dataset containing data on employee turnover.

  • Collected data from kaggle: 9,000+ employees, 10 features
  • Conducted EDA within RStudio
  • Trained various models (Decision Tree, Random Forest, Gradiant Boost, Adaboost, Radial SVM, Polynomial SVM, Logistic Regression, Neural Network)
  • Based on performance metrics (validation AUC, accuracy, precision, and recall), chose a Random forest model with 86.4% accuracy.

VIEW PROJECT REPORT HERE

Leave a Comment

Your email address will not be published. Required fields are marked *