The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICS AND COMPUTERS IN SIMULATION
Transactions ID Number: 20-693
Full Name: Somkid Amornsamankul
Position: Assistant Professor
Age: ON
Sex: Male
Address: Department of Mathematics, Faculty of Science, Mahidol University
Country: THAILAND
Tel: 022015339
Tel prefix: 66
Fax: -
E-mail address: scsam@mahidol.ac.th
Other E-mails: pawalai@yahoo.com
Title of the Paper: Solving multiclass classification problems using combining complementary neural networks and error-correcting output codes
Authors as they appear in the Paper: Somkid Amornsamankul,Jairaj Promrak, Pawalai Kraipeerapun
Email addresses of all the authors: scsam@mahidol.ac.th,jpjairaj@gmail.com,pawalai@yahoo.com
Number of paper pages: 8
Abstract: This paper presented an innovative method, combining Complementary Neural Networks (CMTNN) and Error-Correcting Output Codes (ECOC), to solve multiclass classification problem. CMTNN consist of truth neural network and falsity neural network created based on truth and falsity information, respectively. Two forms of ECOC, exhaustive code and random ECOC, are considered to deal with k-class classification problem. Exhaustive code is applied to the problem with 3 <= k <= 7 whereas random ECOC is used for k > 7. In the experiment, we deal with feed-forward backpropagation neural networks, trained using 10 fold cross-validation method and classified based on two decoding techniques: minimum distance and T > F. The proposed approach has been tested with six benchmark problems: balance, vehicle, nursery, Ecoli, yeast and vowel from the UCI machine learning repository. Three data sets: balance, vehicle and nursery are dealt with exhaustive code while random ECOC is applied!
for Ecoli, yeast and vowel. It was found that our approach provides better performance compared to the existing techniques considering on either CMTNN or ECOC.
Keywords: Multiclass classification problem, Neural network,Feed forward backpropagation, Complementary neural networks,Error-correcting output codes, Exhaustive codes
EXTENSION of the file: .pdf
Special (Invited) Session: Combining Complementary Neural Network and Error-Correcting Output Codes for Multiclass Classification Problems
Organizer of the Session: 653-129
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IP ADDRESS: 119.63.65.147
