Employee Attrition Prediction

06/19/2018
by   Rahul Yedida, et al.
0

We aim to predict whether an employee of a company will leave or not, using the k-Nearest Neighbors algorithm. We use evaluation of employee performance, average monthly hours at work and number of years spent in the company, among others, as our features. Other approaches to this problem include the use of ANNs, decision trees and logistic regression. The dataset was split, using 70 for training the algorithm and 30 94.32

READ FULL TEXT

page 1

page 2

page 3

research
03/03/2019

Stability of decision trees and logistic regression

Decision trees and logistic regression are one of the most popular and w...
research
11/10/2021

Classification of the Chess Endgame problem using Logistic Regression, Decision Trees, and Neural Networks

In this study we worked on the classification of the Chess Endgame probl...
research
04/01/2021

Famous Companies Use More Letters in Logo:A Large-Scale Analysis of Text Area in Logo

This paper analyzes a large number of logo images from the LLD-logo data...
research
03/24/2022

Semantic system for searching of employees

Many people have stress to leave their job and start a new one because o...
research
03/27/2018

A Decision Tree Approach to Predicting Recidivism in Domestic Violence

Domestic violence (DV) is a global social and public health issue that i...
research
11/28/2019

Qini-based Uplift Regression

Uplift models provide a solution to the problem of isolating the marketi...
research
12/22/2021

Predicting Breakdown Risk Based on Historical Maintenance Data for Air Force Ground Vehicles

Unscheduled maintenance has contributed to longer downtime for vehicles ...

Please sign up or login with your details

Forgot password? Click here to reset