The combination evaluation method based on DEA and SVM

Author

Niu, Dong-xiao ; Wang, Xiu-mei ; Gao, Chong

Author_Institution

Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding

Volume

2

fYear

2008

fDate

12-15 July 2008

Firstpage

845

Lastpage

850

Abstract

SVM has the convenient superiority in the classification. But the insufficiency is required the classed samples ahead of time. This affects its widespread application. The paper tries to take full of DEA methodpsilas objective advantages and SVM modelpsilas machine learning advantages. Using DEA method classes the samples data, so as to the training samples have strong reliability. Then, multi-layer SVM is used to evaluate teaching efficiency. In order to verify the effectiveness of the method, 40 faculties are used, which include 34 samples and 6 for experiment. The experimental results show that this method has strong objectivity and impartiality, the combination evaluation method is simple and easy to popularize.

Keywords

data envelopment analysis; support vector machines; data envelope analysis; machine learning; multilayer SVM; samples data; support vector machine; Cybernetics; Data analysis; Data envelopment analysis; Decision making; Education; Electronic mail; Learning systems; Machine learning; Support vector machine classification; Support vector machines; Data envelope analysis (DEA); Evaluation; Support vector machines (SVM);

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICMLC.2008.4620522

Filename

4620522