Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10884737 | Biosystems | 2005 | 4 Pages |
Abstract
Overfitting in multilayer perceptron (MLP) training is a serious problem. The purpose of this study is to avoid overfitting in on-line learning. To overcome the overfitting problem, we have investigated feeling-of-knowing (FOK) using self-organizing maps (SOMs). We propose MLPs with FOK using the SOMs method to overcome the overfitting problem. In this method, the learning process advances according to the degree of FOK calculated using SOMs. The mean square error obtained for the test set using the proposed method is significantly less than that in a conventional MLP method. Consequently, the proposed method avoids overfitting.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Modelling and Simulation
Authors
Kazushi Murakoshi,