A revisit of reducing hidden nodes in a radial basis function neural network with histogram

Pey Yun Goh, Shing Chiang Tan, Wooi Ping Cheah

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

In previous work [1], an incremental radial basis function network trained by a dynamic decay adjustment algorithm (RBFNDDA) was integrated with histogram to reduce redundant hidden neurons (or simply neurons). In order to remove unnecessary neurons, a weight-based indicator was utilized [1]. This hybrid model (RBFNDDA-HIST1) can reduce unnecessary neurons and maintain classification accuracy satisfactorily. However, another aspect of noises, i.e., overlapping among neurons of different classes in RBFNDDA-HIST1 and RBFNDDA, is not tackled fully for solutions. To close this research gap, another version of RBFNDDA-HIST (i.e., RBFNDDA-HISTR) is developed whereby the radius of a neuron (that overlaps with neurons of other classes) is checked before removing it from the network. Several public data sets that have a high level of overlapping records according to an overlapping indicator are used to evaluate the performance of RBFNDDA-HISTR in terms of number of neurons and classification accuracy. A performance comparison among RBFNDDA, RBFNDDA-HISTR and RBFNDDA-HIST1 are made. The results show that the proposed RBFNDDA-HISTR can reduce the number of neurons from RBFNDDA-HIST1 without deteriorating classification accuracy.

Original languageEnglish
Title of host publicationNeural Information Processing - 25th International Conference, ICONIP 2018, Proceedings
EditorsAndrew Chi Sing Leung, Seiichi Ozawa, Long Cheng
PublisherSpringer Verlag
Pages722-731
Number of pages10
ISBN (Print)9783030041786
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event25th International Conference on Neural Information Processing, ICONIP 2018 - Siem Reap, Cambodia
Duration: 13 Dec 201816 Dec 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11302 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Neural Information Processing, ICONIP 2018
Country/TerritoryCambodia
CitySiem Reap
Period13/12/1816/12/18

Keywords

  • Histogram
  • Pruning
  • Radius
  • RBFNDDA
  • Weight

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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