The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 89-547
Full Name: Hyontai Sug
Position: Associate Professor
Age: ON
Sex: Male
Address: Division of Computer & Information Engineering, Dongseo University, Busan, 617-716
Country: KOREA
Tel: 82-51-320-1733
Tel prefix:
Fax: 82-51-327-8955
E-mail address: hyontai@yahoo.com
Other E-mails: shtdaum@hanmail.net
Title of the Paper: Investigating Better Multi-layer Perceptrons for the Task of Classification
Authors as they appear in the Paper: Hyontai Sug
Email addresses of all the authors: hyontai@yahoo.com
Number of paper pages: 10
Abstract: The task of deciding proper sample sizes for multi-layer perceptrons tends to be arbitrary so that, depending on sample data sets, the performance of trained multi-layer perceptrons has a tendency of some fluctuation. As sample size grows, multi-layer perceptrons have the property that performance in prediction accuracy becomes better slowly with some fluctuation. In order to exploit this property this paper suggests a progressive and repeated sampling technique for better multi-layer perceptrons to cope with the fluctuation of prediction accuracy that depend on samples as well as the size of samples. Experiments with six different data sets in UCI machine learning repository showed very good results.
Keywords: Multi-layer perceptrons, neural networks, data mining, classification
EXTENSION of the file: .pdf
Special (Invited) Session: An Effective Sampling Scheme for Better Multi-layer Perceptrons
Organizer of the Session: 640-820
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IP ADDRESS: 118.39.140.246
