A Novel Improvement of Neural Network Classification Using Further Division of Partition Space
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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.
KeywordsClassification neural network partition space further division
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- 1.Qinlan, J.R.: Introduction of decision trees. Machine Learning 1, 86–106 (1986)Google Scholar
- 6.Kennedy, J., Eberhart, R.C.: A new optimizer using paritcle swarm theory. In: Proceeding of the Sixth Int. Symposium on Micromachine and Human Science, Nagoya, Japan, pp. 39–43 (1995)Google Scholar
- 7.DeSilva, C.J.S., et al.: Artificial Neural networks and Breast Cancer Prognosis. The Australian Computer Journal 26, 78–81 (1994)Google Scholar
- 9.Jain, R., Abraham, A.: A Comparative Study of Fuzzy Classifiers on Breast Cancer Data. Australiasian Physical And Engineering Sciences in Medicine, Australia 27(4), 147–152 (2004)Google Scholar