Improving constructive training of RBF networks through selective pruning and model selection
This letter proposes a constructive training method for radial basis function networks. The proposed method is an extension of the dynamic decay adjustment (DDA) algorithm, a fast constructive algorithm for classification problems. The proposed method, which is based on selective pruning and DDA mod...
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| Vydané v: | Neurocomputing (Amsterdam) Ročník 64; s. 537 - 541 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.03.2005
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| ISSN: | 0925-2312, 1872-8286 |
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| Abstract | This letter proposes a constructive training method for radial basis function networks. The proposed method is an extension of the dynamic decay adjustment (DDA) algorithm, a fast constructive algorithm for classification problems. The proposed method, which is based on selective pruning and DDA model selection, aims to improve the generalization performance of DDA without generating larger networks. Simulations using four image recognition datasets from the UCI repository demonstrate the validity of the proposed method. |
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| AbstractList | This letter proposes a constructive training method for radial basis function networks. The proposed method is an extension of the dynamic decay adjustment (DDA) algorithm, a fast constructive algorithm for classification problems. The proposed method, which is based on selective pruning and DDA model selection, aims to improve the generalization performance of DDA without generating larger networks. Simulations using four image recognition datasets from the UCI repository demonstrate the validity of the proposed method. |
| Author | Melo, Bruno J.M. Meira, Silvio R.L. Oliveira, Adriano L.I. |
| Author_xml | – sequence: 1 givenname: Adriano L.I. surname: Oliveira fullname: Oliveira, Adriano L.I. email: alio@cin.ufpe.br organization: Polytechnic School, University of Pernambuco, Rua Benfica, 455, Madalena, Recife - PE 50.750-410, Brazil – sequence: 2 givenname: Bruno J.M. surname: Melo fullname: Melo, Bruno J.M. organization: Polytechnic School, University of Pernambuco, Rua Benfica, 455, Madalena, Recife - PE 50.750-410, Brazil – sequence: 3 givenname: Silvio R.L. surname: Meira fullname: Meira, Silvio R.L. organization: Center of Informatics, Federal University of Pernambuco, P.O. Box 7851, Cidade Universitaria, Recife - PE 50.732-970, Brazil |
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| CitedBy_id | crossref_primary_10_1016_j_neucom_2007_11_003 crossref_primary_10_3390_ai3030044 crossref_primary_10_5402_2012_324194 crossref_primary_10_1016_j_advengsoft_2008_12_020 crossref_primary_10_1007_s00521_011_0546_1 crossref_primary_10_1016_j_neucom_2006_04_007 crossref_primary_10_1007_s00521_007_0169_8 crossref_primary_10_1016_j_neucom_2006_01_004 |
| Cites_doi | 10.1016/j.neucom.2003.12.004 10.1016/S0925-2312(97)00063-5 10.1109/ICPR.2004.1333850 10.1109/IJCNN.2004.1380945 |
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| Keywords | RBF network Neural network Model complexity Classification |
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| References | M.R. Berthold, J. Diamond, Boosting the performance of RBF networks with dynamic decay adjustment, in: G. Tesauro, D. Touretzky, T. Leen, (Eds.), Advances in Neural Information Processing, vol. 7, MIT Press, New York, 1995, pp. 521–528. A.L.I. Oliveira, F.B.L. Neto, S.R.L. Meira, Improving RBF-DDA performance on optical character recognition through parameter selection, in: Proceedings of the 17th International Conference on Pattern Recognition (ICPR’2004), vol. 4, pp. 625–628. (1998). C. Blake, C. Merz, UCI repository of machine learning databases, Available from Paetz (bib5) 2004; 62 Berthold, Diamond (bib2) 1998; 19 A.L.I. Oliveira, F.B.L. Neto, S.R.L. Meira, Improving novelty detection in short time series through RBF-DDA parameter adjustment, in: Proceedings of International Joint Conference on Neural Networks (IJCNN’2004), IEEE Press. 10.1016/j.neucom.2004.11.027_bib1 Berthold (10.1016/j.neucom.2004.11.027_bib2) 1998; 19 10.1016/j.neucom.2004.11.027_bib3 10.1016/j.neucom.2004.11.027_bib4 10.1016/j.neucom.2004.11.027_bib6 Paetz (10.1016/j.neucom.2004.11.027_bib5) 2004; 62 |
| References_xml | – volume: 19 start-page: 167 year: 1998 end-page: 183 ident: bib2 article-title: Constructive training of probabilistic neural networks publication-title: Neurocomputing – reference: ] (1998). – volume: 62 start-page: 79 year: 2004 end-page: 91 ident: bib5 article-title: Reducing the number of neurons in radial basis function networks with dynamic decay adjustment publication-title: Neurocomputing – reference: C. Blake, C. Merz, UCI repository of machine learning databases, Available from [ – reference: M.R. Berthold, J. Diamond, Boosting the performance of RBF networks with dynamic decay adjustment, in: G. Tesauro, D. Touretzky, T. Leen, (Eds.), Advances in Neural Information Processing, vol. 7, MIT Press, New York, 1995, pp. 521–528. – reference: A.L.I. Oliveira, F.B.L. Neto, S.R.L. Meira, Improving novelty detection in short time series through RBF-DDA parameter adjustment, in: Proceedings of International Joint Conference on Neural Networks (IJCNN’2004), IEEE Press. – reference: A.L.I. Oliveira, F.B.L. Neto, S.R.L. Meira, Improving RBF-DDA performance on optical character recognition through parameter selection, in: Proceedings of the 17th International Conference on Pattern Recognition (ICPR’2004), vol. 4, pp. 625–628. – ident: 10.1016/j.neucom.2004.11.027_bib1 – ident: 10.1016/j.neucom.2004.11.027_bib6 – volume: 62 start-page: 79 year: 2004 ident: 10.1016/j.neucom.2004.11.027_bib5 article-title: Reducing the number of neurons in radial basis function networks with dynamic decay adjustment publication-title: Neurocomputing doi: 10.1016/j.neucom.2003.12.004 – volume: 19 start-page: 167 year: 1998 ident: 10.1016/j.neucom.2004.11.027_bib2 article-title: Constructive training of probabilistic neural networks publication-title: Neurocomputing doi: 10.1016/S0925-2312(97)00063-5 – ident: 10.1016/j.neucom.2004.11.027_bib3 doi: 10.1109/ICPR.2004.1333850 – ident: 10.1016/j.neucom.2004.11.027_bib4 doi: 10.1109/IJCNN.2004.1380945 |
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| SubjectTerms | Classification Model complexity Neural network RBF network |
| Title | Improving constructive training of RBF networks through selective pruning and model selection |
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