Employee_Attrition
Predicting employee attrition using HR data
Business Requirement
Predict the employee attrition using the HR data.
ML Requirement
Attrition is the target variable represented as a Boolean field. Using features provided in the CSV file predict whether the employee will leave the organisation or not.
Assumptions
- Since we do not have test data separately, we will use the Train-Test Split from SciKit-Learn for generating the test data (used to compute the performance metrics).
- Data is fictional and can result in a very low accuracy score- we will then opt for some-other metrics for model evaluation.
- There is no Time-Series data for the attrition of employees which will result in some deviation.
Contents
- Correlation Heatmap - to explain the relation in various parameters
- Project Report - tracking the status and lifecycle of project
- Employee Attrition Predictor - IPython notebook
- HR-Employee-Attrition - Data file taken from https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset
- Visualization plots are added in file Visualization
Algorithms used
- Logistic Regression
- Random Forest
Encoder used
- Label Encoder
- One Hot Encoder
Note:
I welcome any suggestions or recommendation to make this project better. Also I am working on the visualization part too.