A robust model based on space-partitioning method

A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of expe...

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Published inNeural Information Processing: 6th International Conference, 1999 Vol. 3; pp. 992 - 997 vol.3
Main Authors Liming Zhang, Weiping Fan
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
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ISBN9780780358713
0780358716
DOI10.1109/ICONIP.1999.844671

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Abstract A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.
AbstractList A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.
Author Weiping Fan
Liming Zhang
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Snippet A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of...
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StartPage 992
SubjectTerms Analytical models
Convergence
Handwriting recognition
Multilayer perceptrons
Neural networks
Neurons
Partial response channels
Partitioning algorithms
Robustness
Title A robust model based on space-partitioning method
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