A Multi-Level Probabilistic Neural Network

Authors:
Ning Zong;Xia Hong
Affiliations:
School of Systems Engineering, University of Reading, RG6 6AY, UK;School of Systems Engineering, University of Reading, RG6 6AY, UK
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Abstract

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.