Attrition_cb01_gold_hd_2018

To analyze attrition effectively, focus on these common data categories: Age, Gender, Marital Status.

The dataset contains employee information and a binary target variable ( Attrition ) indicating whether an employee stayed or left the company. The "2018" and "Gold" designations usually refer to a cleaned, feature-engineered version of the standard IBM HR analytics data. 2. Core Features Attrition_cb01_gold_HD_2018

This guide outlines the core components of the dataset and how to use it for predictive modeling. 1. Dataset Overview To analyze attrition effectively, focus on these common

Monthly Income, Percent Salary Hike, Stock Option Level. Dataset Overview Monthly Income, Percent Salary Hike, Stock

Environment Satisfaction, Job Satisfaction, Relationship Satisfaction, Work-Life Balance. 3. Exploratory Data Analysis (EDA)

Lower monthly income is often the strongest predictor of leaving.

Years at Company, Years in Current Role, Performance Rating, Training Times Last Year.