Open AccessThe Application of The Decision Tree Algorithm Based on K-means in Employee Turnover Prediction
Author(s) -
Yunmeng Zhang,
Chengyi Zhang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012123
Subject(s) - turnover , decision tree , human resource management , computer science , inventory turnover , decision tree learning , human resources , tree (set theory) , operations research , knowledge management , business , data mining , mathematics , management , economics , finance , mathematical analysis , stock exchange
The employee’s voluntary turnover is one of the most difficult problems for the company. The research uses a human resource data as an example. K-means is used to classify employees, and then each type of the decision tree algorithm is used to conduct prediction and analysis of turnover. After research and analysis according to the experimental results, the two types of employees with high turnover rate are analyzed, and the management is provided with measures to prevent the occurrence of some acts of turnover.