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Multi-class contour preserving classification

by Piyabute Fuangkhon; Thitipong Tanprasert

Title:

Multi-class contour preserving classification

Author(s):

Piyabute Fuangkhon
Thitipong Tanprasert

Issued date:

2012-08

Citation:

International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’12), Natal, Brazil, 29-31 August 2012 Lecture Notes in Computer Science LNCS 7435, Springer Berlin / Heidelberg pp. 35-42, ISSN: 0302-9743 (print), ISBN: 978-3-642-32638-7, doi:10.1007/978-3-642-32639-4_5.

Abstract:

The original contour preserving classification technique was proposed to improve the robustness and weight fault tolerance of a neu- ral network applied with a two-class linearly separable problem. It was recently found to be improving the level of accuracy of two-class classi- fication. This paper presents an augmentation of the original technique to improve the level of accuracy of multi-class classification by better preservation of the shape or distribution model of a multi-class problem. The test results on six real world multi-class datasets from UCI ma- chine learning repository present that the proposed technique supports multi-class data and can improve the level of accuracy of multi-class classification more effectively.

Keyword(s):

Contour preserving classification
Data preprocessor
Neural networks (Computer science)
Outpost vector
Pattern classification

Resource type:

Conference Paper

Extent:

8 pages

Type:

Text

File type:

application/pdf

Language:

eng

Rights holder(s):

Piyabuth Fuangkhon
Thitipong Tanprasert

URI:

http://repository.au.edu/handle/6623004553/20662
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  • Conference Papers [24]


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Copyright © Assumption University.
All Rights Reserved.

Contact Us

The St. Gabriel's Library   
Hua Mak Campus  
Ramkhamhaeng 24, Hua Mak  
Bangkok Thailand 10240  
Tel.: (662) 3004543-62 Ext. 3402  
Fax.: (662) 7191544  
E-Mail Library : library@au.edu  


The Cathedral of Learning Library
Suvarnabhumi Campus
Bang Na-Trad Km. 26 Bangsaothong
Samuthprakarn Thailand 10540
Tel.: (662) 7232024, 7232025
Fax.: (662) 7191544
E-Mail Library : library@au.edu
 

 

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