/Prediction-of-Employee-Attrition

Primary LanguageJupyter Notebook

Employee-Attrition - Classification

The objective of this project was to predict the rate of employee attrition in the current scenario based on different features. It was the classification problem. I performed EDA, Feature Scaling, Feature Engineering and applied Logistics Regression, Decision Tree and Random Forest for prediction.I got high accuracy score about 0.97 using random Forest.

Steps:

  • Import Libraries and read data set
  • Describe the dataset
  • Data Transforamtion / Categorical to Numerical
  • Data Cleaning and Feature Selection
  • Split the dataset into train and test set
  • Machine Learning Modeling
  • train the model (Fit)
  • Test the trained model (prediction )
  • Model Evaluation
  • Model Deployment Using Gradio