Research On The Application Of Data Mining Technology In Human Resource Management System

In recent years,the application of Data Mining Technology has played an important role in many fields.Many scholars and enterprises have begun to focus on applying Data Mining Technology in Human Resource Management System to help companies’ sustainable development.The application of Data Mining Technology in the Human Resource Management System can be used to help companies to mine high-value information hidden behind the data,assist companies to accurately assess their own level and predict possible risks,which will be the mainstream trend in the development of modern Human Resource Management System.This article focuses on the application of Data Mining Technology in Human Resource Management System,which innovatively uses Data Visualization Technology in the research process to promote the convenience and intuitiveness of data display.The main research contents are as follows:(1)Analyze the feasibility and practical significance of the application of Data Mining Technology in Human Resource Management System,focus on the algorithms commonly used in the field of Data Mining and combine with the needs of human resource management practice to propose specific algorithm application scenarios and implementation ideas.For example,the application of Multiple Linear Regression algorithm to establish the human resource demand prediction model,the application of K-means algorithm to establish the enterprise employee performance evaluation model,and the application of Association Rules algorithm to mine the enterprise’s human resource structure,etc.(2)Combine Data Visualization Technology with Human Resource Management System and Data Mining Technology to explore the application of Data Visualization Technology in system data display and data mining process.It can not only help human resource managers to analyze data more conveniently and decision-making,but also provide important auxiliary functions for the data mining process by intuitively and multi-dimensionally presenting information such as data distribution,association,and abnormality.(3)Use Data Mining and Visualization Techniques to build and evaluate employee turnover prediction models.Through the Data Visualization Technology,the data selected from the Human Resource Management System are descriptive analyzed.The Stratified Sampling Method and the 10-fold Cross-validation Method are used to promote the stability of the data model.the Naive Bayes algorithm and CART Decision Tree algorithm are selected to build the data mining model.Through the comprehensive evaluation of accuracy,precision and recall index,it is found that the CART Decision Tree Model has excellent prediction effect,and the three evaluation indexes have reached more than 94%.