Skip to content
#

logistic-regression

Here are 8,093 public repositories matching this topic...

Dataset Analysis and Preprocessing: Download the IBM HR Analytics Employee Attrition & Performance dataset from a reputable source (e.g., Kaggle). Analyze the dataset to understand its structure and features. It contains various attributes related to employee demographics, job roles, satisfaction levels, performance ratings, etc., along with a targ

  • Updated May 11, 2024
  • Jupyter Notebook

This project employs logistic regression and advanced analytics to predict employee attrition, enhancing organizational productivity. Leveraging machine learning, it develops a robust model using features like age, job satisfaction, and work environment. Through EDA, feature engineering, and grid search model tuning, it optimizes performance metric

  • Updated May 9, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the logistic-regression topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the logistic-regression topic, visit your repo's landing page and select "manage topics."

Learn more