The comparison and analysis of classification methods for psychological assessment data

Author

Song, Qu

Author_Institution

School Of Computer Science and Technology, China University of Mining and Technology, CUMT, XUZHOU, CHINA

fYear

2010

fDate

4-6 Dec. 2010

Firstpage

4133

Lastpage

4135

Abstract

Mental health is currently subject to extensive social concern. Applying the psychological assessment to determine the individual psychological characteristics has already become an important method for early psychological intervention; therefore, the efficiency of Psychological assessment data classification is an important measurement for the effect of psychological evaluation. To address the problem, the author has researched the psychological assessment data through experiment based on the evaluation of 455 students of China University of Mining and Technology. Because the psychological assessment data is characterized as higher dimensions, form discrete and uneven sample distribution, this article has compared and analyzed several common classification measurements, and then put forward the improved methods to suit the characteristics of the data sets.

Keywords

Accuracy; Algorithm design and analysis; Classification algorithms; Machine learning algorithms; Psychology; Support vector machines; Training; Bayes algorithm Introduction; KNN algorithm; Psychological assessment classification; SVM algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Engineering (ICISE), 2010 2nd International Conference on

Conference_Location

Hangzhou, China

Print_ISBN

978-1-4244-7616-9

Type

conf

DOI

10.1109/ICISE.2010.5690602

Filename

5690602