Weighted clone selection algorithm based on rough set theory

被引：1

作者：

Wu, Jia ^{[1
]}

Cai, Zhihua ^{[1
]}

Chen, Xiaolin ^{[1
]}

Li, Meng ^{[1
]}

Guo, Bin ^{[2
]}

机构：

[1] School of Computer Science, China University of Geosciences

[2] School of Computer Science, University of Sydney

来源：

Journal of Software | 2013年 / 8卷 / 06期

关键词：

Attribute weight; Classification; Clone selection; Rough set theory;

D O I：

10.4304/jsw.8.6.1333-1338

中图分类号：

学科分类号：

摘要：

Clone selection is a new artificial intelligence technology, with self-organization, self-learning, selfrecognition, self-memory capacity. In the traditional clone selection algorithm for data classification, all the attributes for classification have the same influence, which affects its classification performance to some extent, given an appropriate weight for each attribute value can modify this imbalance. Accordingly this, proposes a weighted clone selection algorithm based on rough set to improve the performance of clone selection. In weighted clone selection algorithm attribute weights obtained directly from the training data using rough set theory, the attribute weights was used to test Data classification. Then verify the validity of the method by the experiments of UCI data sets. © 2013 ACADEMY PUBLISHER.

引用

页码：1333 / 1338

页数：5

共 12 条

[1]

Qin F., Ren S.L., Cheng Z.K., Luo H., Attribute weighted Naïve Bayes classification, Computer Engineering and Applications, 44, 6, pp. 107-109, (2008)

[2]

Feng R.Y., Shang T.H., Liu H.C., An attribute weighting K-means alforithm based on mean-squaredeviation, Information Technology, 3, pp. 55-57, (2010)

[3]

de Castro L.N., Timmis J., Artificial Immune Systems: A New Computational Intelligence Approach, (2002)

[4]

Brownlee J., Clonal Selection Theory &Clonalg the Clonal Selection Classification Algorithm, (2005)

[5]

Yuan G.L., Liu J.Z., The Design for Feed Water System of Boiler Based on Fuzzy Immune Smith Control, Journal of Computers, 7, 1, pp. 278-283, (2012)

[6]

de Castro L.N., Von Zuben F.J., Learning and Optimization Using the Clonal Selection Principle, IEEE Transactions On Evolutionary Computation, Special Issue On Artificial Immune Systems, 6, pp. 239-251, (2002)

[7]

Wu J., Cai Z., Ao S., Hybrid Dynamic K-Nearest- Neighbor and Distance and Attribute Weighted Method for Classification, International Journal of Computer Applications In Technology, 43, 4, pp. 378-384, (2012)

[8]

Wu J., Cai Z., Attribute Weighting via Differential Evolution Algorithm for Attribute Weighted Naive Bayes (WNB), Journal of Computational Information Systems, 7, 5, pp. 1672-1679, (2011)

[9]

Wang D.H., Liu X.W., Jiang L.X., Zhang X.T., Zhao Y.G., Rough Set Approach to Multivariate Decision Trees Inducing, Journal of Computers, 7, 4, pp. 870-879, (2012)

[10]

Merz C., Murphy P., Aha D., UCI Repository of Machine Learning Databases, (1997)

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