Title :
A self-adapting regression SVM model and its application on middle managers performance evaluation
Author_Institution :
Econ. & Manage. Dept., North China Electr. Power Univ., Beijing
Abstract :
It is very important that middle managers work performance affect the survival and development of enterprises, carry on reasonable, scientific and effective performance evaluation, and encourage them to give full play to the initiative and creativity, which is the reliable protection of achieving the enterprises short-term and long-term objectives. Based on the SVM algorithm theory, this paper establish the middle managers performance evaluation model based on self-adapting regression SVM, through establishing middle managers performance index system, use several SVM classifier series portfolio, solve the problems that the training samplespsila category and quantity are imbalance, and the data is interfered, realize the performance evaluation to middle managers. Experimental results show that the method improved the middle managers performance evaluation accuracy and efficiency.
Keywords :
appraisal; personnel; regression analysis; support vector machines; SVM classifier series portfolio; middle managers performance evaluation; performance evaluation model; self-adapting regression SVM model; Conference management; Cybernetics; Electronic mail; Energy management; Kernel; Machine learning; Management training; Power generation economics; Support vector machine classification; Support vector machines; Self-adapting; middle managers; performance evaluation; regression SVM;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620484