DocumentCode :
120286
Title :
Assessing Personal Performance with M-SVMs
Author :
Xude Gui ; Zhongyi Hu ; Jinlong Zhang ; Yukun Bao
Author_Institution :
Sch. of Manage., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2014
fDate :
4-6 July 2014
Firstpage :
598
Lastpage :
601
Abstract :
In view of the significance of personal performance assessment in the working metrics of human resource management, this study proposes to set up a multi-class Support Vector Machine based model to elaborate how to evaluate the staffs´ performance effectively and efficiently. Data samples are collected from a construction company in China, and used to justify the proposed model against the selected well-established classifiers. The experimental results suggest it to be a promising alternative for assessing personal performance.
Keywords :
construction industry; data mining; human resource management; support vector machines; China; M-SVM; construction company; human resource management; multiclass support vector machine; personal performance assessment; working metrics; Companies; Data mining; Decision trees; Educational institutions; Performance evaluation; Support vector machines; Training; data mining; human resource manangement; multi-class SVMs; personeal performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-5371-4
Type :
conf
DOI :
10.1109/CSO.2014.115
Filename :
6923756
Link To Document :
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