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A multi-level probabilistic neural network

Zong, N. and Hong, X. (2007) A multi-level probabilistic neural network. Lecture Notes in Computer Science, 4492. pp. 516-525. ISSN 0302-9743 9783540723929

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Abstract/Summary

Based on the idea of an important cluster, a new multi-level probabilistic neural network (MLPNN) is introduced. The MLPNN uses an incremental constructive approach, i.e. it grows level by level. The construction algorithm of the MLPNN is proposed such that the classification accuracy monotonically increases to ensure that the classification accuracy of the MLPNN is higher than or equal to that of the traditional PNN. Numerical examples are included to demonstrate the effectiveness of proposed new approach.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:15501
Uncontrolled Keywords:STOCHASTIC DISCRIMINATION, CLASSIFICATION, CLASSIFIERS
Additional Information:Proceedings Paper 4th International Symposium on Neural Networks (ISNN 2007) JUN 03-07, 2007 Nanjing, PEOPLES R CHINA

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