m0h1t98 / Employee-Attrition

This project is a machine learning classification problem. 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 tried three algorithms (Logistics, Decision Tree & Random Forest). But I got high accuracy score about 0.97 using random Forest.

Employee-Attrition - Classification

This project is a machine learning classification problem. 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 applied three classification algorithms (Logistics, Decision Tree & Random Forest). But 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