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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 F…

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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

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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 F…

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