R Programming R Practical - Employee Attrition Prediction using Random Forest Technique and R

R Practical - Employee Attrition Prediction using Random Forest Technique and R

Catalog: R Programming
Short name: Employee Attrition Prediction using RFT and R
Course start date: 2024-07-02
Paystack

Description

In this course, we'll discover how Attrition is a major issue in any industry, whether it concerns an organization's employees or an e-commerce site's customers.


The employer will save a lot of time, effort, and money if we can precisely anticipate which customers or employees will leave their current company or organisation. We can then help them find or acquire replacements in advance, which won't hinder the firm's ability to continue to grow.


This chapter presents a comparison of various machine learning techniques, including Naive Bayes, SVM, decision trees, random forests, and logistic regression. The conclusion that has been supplied will assist us in recognising the behaviour of workers who can be dressed over the subsequent occasion. According to experimental findings, the logistic regression methodology can outperform other machine learning methods with an accuracy rate of up to 86%.

Course Duration:-2h 2m

Sections

General
0 activities

Introduction to Employee Attrition Prediction Using Random Forest
Random Forest Overview
Random Forest Overview Continue
Variable Explanation
Variable Explanation Continue
Pre Modelling Steps
Pre Modelling Steps Continue
Model Development
Model Development Continue
Model Tunning
Model Tunning Continue
Tunning and Validation
Course Certificate

Secure Video
12
Certificate
1
Cost: 5000

Tag

Course Duration:-2h 2m