The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 29-662
Full Name: Hyontai Sug
Position: Associate Professor
Age: ON
Sex: Male
Address: Division of Computer and Information Engineering, Dongseo University, Busan, 617-716
Country: KOREA
Tel: 82-10-5071-7143
Tel prefix:
Fax: 82-51-327-8955
E-mail address: hyontai@yahoo.com
Other E-mails: shtdaum@hanmail.net
Title of the Paper: Empirical Determination of Sample Sizes for Multi-layer Perceptrons by Simple RBF Networks
Authors as they appear in the Paper: Hyontai Sug
Email addresses of all the authors: hyontai@yahoo.com
Number of paper pages: 10
Abstract: It¡¯s well known that the computing time to train multilayer perceptrons is very long because of weight space of the neural networks and small amount of adjustment of the wiights for convergence. The matter becomes worse when the size of training data set is large, which is common in data mining tasks. Moreover, depending on samples, the performance of neural networks change. So, in order to determine appropriate sample sizes for multilayer perceptrons this paper suggests an effective approach with the help of simple radial basis function networks that work as a guide. Experiments with the two different data sets that may represent business and scientific domain well showed the effectiveness of the suggested method.
Keywords: multilayer perceptron, sample size, radial basis function network, data mining
EXTENSION of the file: .pdf
Special (Invited) Session: A Pilot Sampling Method for Multi-layer Perceptrons
Organizer of the Session: 620-655
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IP ADDRESS: 118.39.140.5
