کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10884737 | 1079486 | 2005 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Avoiding overfitting in multilayer perceptrons with feeling-of-knowing using self-organizing maps
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
مدلسازی و شبیه سازی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Avoiding overfitting in multilayer perceptrons with feeling-of-knowing using self-organizing maps Avoiding overfitting in multilayer perceptrons with feeling-of-knowing using self-organizing maps](/preview/png/10884737.png)
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosystems - Volume 80, Issue 1, April 2005, Pages 37-40
Journal: Biosystems - Volume 80, Issue 1, April 2005, Pages 37-40
نویسندگان
Kazushi Murakoshi,