My task is to develop a machine learning model for predicting employee attrition using historical data, which includes employee demographic information and job-related details. The objective is to evaluate the model's performance using appropriate metrics. The project involves the following steps:
- Data Wrangling
- Exploratory Data Analysis (EDA)
- Data Pre-processing
- Hypothesis Testing
- Feature Selection
- Logistic Regression Model
The goal is to enhance the accuracy and effectiveness of the predictive models through thorough analysis and application of appropriate statistical methods. By systematically addressing each step, we aim to create a robust model that can provide valuable insights into employee attrition factors and contribute to informed decision-making.