A hybrid projection based and Radial Basis Function architecture

Shimon Cohen; Nathan Intrator

doi:10.1007/3-540-45014-9_14

A hybrid projection based and Radial Basis Function architecture

Shimon Cohen^*, Nathan Intrator

^*Corresponding author for this work

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].

Original language	English
Title of host publication	Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings
Editors	Josef Kittler, Fabio Roli
Publisher	Springer Verlag
Pages	147-156
Number of pages	10
ISBN (Print)	3540677046, 9783540677048
DOIs	https://doi.org/10.1007/3-540-45014-9_14
State	Published - 2000
Event	1st International Workshop on Multiple Classifier Systems, MCS 2000 - Cagliari, Italy Duration: 21 Jun 2000 → 23 Jun 2000

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1857 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Multiple Classifier Systems, MCS 2000
Country/Territory	Italy
City	Cagliari
Period	21/06/00 → 23/06/00

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10.1007/3-540-45014-9_14

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Cohen, S., & Intrator, N. (2000). A hybrid projection based and Radial Basis Function architecture. In J. Kittler, & F. Roli (Eds.), Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings (pp. 147-156). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1857 LNCS). Springer Verlag. https://doi.org/10.1007/3-540-45014-9_14

Cohen, Shimon ; Intrator, Nathan. / A hybrid projection based and Radial Basis Function architecture. Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings. editor / Josef Kittler ; Fabio Roli. Springer Verlag, 2000. pp. 147-156 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A hybrid projection based and Radial Basis Function architecture",

abstract = "A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].",

author = "Shimon Cohen and Nathan Intrator",

year = "2000",

doi = "10.1007/3-540-45014-9_14",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "147--156",

editor = "Josef Kittler and Fabio Roli",

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Cohen, S & Intrator, N 2000, A hybrid projection based and Radial Basis Function architecture. in J Kittler & F Roli (eds), Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1857 LNCS, Springer Verlag, pp. 147-156, 1st International Workshop on Multiple Classifier Systems, MCS 2000, Cagliari, Italy, 21/06/00. https://doi.org/10.1007/3-540-45014-9_14

A hybrid projection based and Radial Basis Function architecture. / Cohen, Shimon; Intrator, Nathan.

Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings. ed. / Josef Kittler; Fabio Roli. Springer Verlag, 2000. p. 147-156 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1857 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Intrator, Nathan

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N2 - A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].

AB - A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].

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BT - Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings

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Cohen S, Intrator N. A hybrid projection based and Radial Basis Function architecture. In Kittler J, Roli F, editors, Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings. Springer Verlag. 2000. p. 147-156. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45014-9_14

A hybrid projection based and Radial Basis Function architecture

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