Pattern Classification Based on RBF Networks with Self-Constructing Clustering and Hybrid Learning

Author:

He Zan-Rong,Lin Yan-Ting,Wu Chen-Yu,You Ying-Jie,Lee Shie-Jue

Abstract

Radial basis function (RBF) networks are widely adopted to solve problems in the field of pattern classification. However, in the construction phase of such networks, there are several issues encountered, such as the determination of the number of nodes in the hidden layer, the form and initialization of the basis functions, and the learning of the parameters involved in the networks. In this paper, we present a novel approach for constructing RBF networks for pattern classification problems. An iterative self-constructing clustering algorithm is used to produce a desired number of clusters from the training data. Accordingly, the number of nodes in the hidden layer is determined. Basis functions are then formed, and their centers and deviations are initialized to be the centers and deviations of the corresponding clusters. Then, the parameters of the network are refined with a hybrid learning strategy, involving hyperbolic tangent sigmoid functions, steepest descent backpropagation, and least squares method. As a result, optimized RBF networks are obtained. With this approach, the number of nodes in the hidden layer is determined and basis functions are derived automatically, and higher classification rates can be achieved. Furthermore, the approach is applicable to construct RBF networks for solving both single-label and multi-label pattern classification problems.

Funder

Ministry of Science and Technology, Taiwan

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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1. Matrix Hyper-Basis Function Neural Network and Its Online Learning;2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS);2023-09-07

2. Estimation of Radial Basis Function Network Centers via Information Forces;Entropy;2022-09-23

3. Classifying Speech into Offensive and Hate Categories along with Targeted Communities using Machine Learning;2022 International Conference on Inventive Computation Technologies (ICICT);2022-07-20

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