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Contour Plots of Objective Functions for Feed-Forward Neural Networks

INTERNATIONAL JOURNAL OF CONTENTS / INTERNATIONAL JOURNAL OF CONTENTS, (P)1738-6764; (E)2093-7504
2012, v.8 no.4, pp.30-35
https://doi.org/10.5392/IJoC.2012.8.4.030

Abstract

Error surfaces provide us with very important information for training of feed-forward neural networks (FNNs). In this paper, we draw the contour plots of various error or objective functions for training of FNNs. Firstly, when applying FNNs to classifications, the weakness of mean-squared error is explained with the viewpoint of error contour plot. And the classification figure of merit, mean log-square error, cross-entropy error, and n-th order extension of cross-entropy error objective functions are considered for the contour plots. Also, the recently proposed target node method is explained with the viewpoint of contour plot. Based on the contour plots, we can explain characteristics of various error or objective functions when training of FNNs proceeds.

keywords
Feed-forward Neural Network, Error Function, Objective Function, Contour Plot.

INTERNATIONAL JOURNAL OF CONTENTS