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A Novel Improvement of Neural Network Classification Using Further Division of Partition Space

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4527)

Abstract

Further Division of Partition Space (FDPS) is a novel technique for neural network classification. Partition space is a space that is used to categorize data sample after sample, which are mapped by neural network learning. The data partition space, which are divided manually into few parts to categorize samples, can be considered as a line segment in the traditional neural network classification. It is proposed that the performance of neural network classification could be improved by using FDPS. In addition, the data partition space are to be divided into many partitions, which will attach to different classes automatically. Experiment results have shown that this method has favorable performance especially with respect to the optimization speed and the accuracy of classified samples.

Keywords

Classification neural network partition space further division 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  1. 1.School of Information Science and Engineering, University of Jinan, JinanChina
  2. 2.Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and TechnologyNorway

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