Probabilistic neural-network structure determination for pattern classification

被引：197

作者：

Mao, KZ ^{[1
]}

Tan, KC ^{[1
]}

Ser, W ^{[1
]}

机构：

[1] Nanyang Technol Univ, Ctr Signal Proc, Singapore 2263, Singapore

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2000年 / 11卷 / 04期

关键词：

genetic algorithms; orthogonal algorithm; pattern classification; probabilistic neural network (PNN);

D O I：

10.1109/72.857781

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Network structure determination is an important issue in pattern classification based on a probabilistic neural network. In this study, a supervised network structure determination algorithm is proposed. The proposed algorithm consists of two parts and runs in an iterative way. The first part identifies an appropriate smoothing parameter using a genetic algorithm, while the second part determines suitable pattern layer neurons using a forward regression orthogonal algorithm. The proposed algorithm is capable of offering a fairly small network structure with satisfactory classification accuracy.

引用

页码：1009 / 1016

页数：8

共 21 条

[1]

[Anonymous], 1989, GENETIC ALGORITHM SE

[2] IDENTIFICATION OF MIMO NON-LINEAR SYSTEMS USING A FORWARD-REGRESSION ORTHOGONAL ESTIMATOR [J].

BILLINGS, SA ;

CHEN, S ;

KORENBERG, MJ .

INTERNATIONAL JOURNAL OF CONTROL, 1989, 49 (06) :2157-2189

[3]

Bishop C. M., 1995, NEURAL NETWORKS PATT

[4] LEARNING VECTOR QUANTIZATION FOR THE PROBABILISTIC NEURAL NETWORK [J].

BURRASCANO, P .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1991, 2 (04) :458-461

[5] ORTHOGONAL LEAST-SQUARES LEARNING ALGORITHM FOR RADIAL BASIS FUNCTION NETWORKS [J].

CHEN, S ;

COWAN, CFN ;

GRANT, PM .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1991, 2 (02) :302-309

[6] Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks [J].

Chen, S ;

Wu, Y ;

Luk, BL .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1999, 10 (05) :1239-1243

[7]

KRAMER C, 1995, P ANN INT C IEEE ENG, V17, P807

[8] Nearest prototype classification: Clustering, genetic algorithms, or random search? [J].

Kuncheva, LI ;

Bezdek, JC .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 1998, 28 (01) :160-164

[9] Performance and efficiency: Recent advances in supervised learning [J].

Ma, S ;

Ji, CY .

PROCEEDINGS OF THE IEEE, 1999, 87 (09) :1519-1535

[10] ON THE GENERALIZATION ABILITY OF NEURAL-NETWORK CLASSIFIERS [J].

MUSAVI, MT ;

CHAN, KH ;

HUMMELS, DM ;

KALANTRI, K .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1994, 16 (06) :659-663

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