Decision trees and random forest models were built using Scikit-learn and Python to train an employee churn prediction application. Kaggle Dataset of Employee Turnover with 15,000 employee Details (Rows) and 10 Features (Columns) was used in this ML model. Interactive controls for tuning Hyperparametres like Depth, min_leaf, min_samples was also developed using ipywidgets and interact in Jupyter notebook.
-
Notifications
You must be signed in to change notification settings - Fork 1
priyanshkedia04/Project-Predict-Employee-Turnover-with-scikit-learn
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Decision trees and Random forests using scikit-learn and Python to build an employee churn prediction application with interactive controls
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published