Comparison of Various Feature Selection Methods in Application to Prototype Best Rules

作者: Marcin Blachnik

DOI: 10.1007/978-3-540-93905-4_31

关键词:

摘要: Prototype based rules is an interesting tool for data analysis. However most of prototype selection methods like CFCM+LVQ algorithm do not have embedded feature and require as initial preprocessing step. The problem that appears which the should be used with method, what advantages or disadvantages certain solutions can pointed out. analysis above problems on empirical

参考文章(12)
Włodzisław Duch, Similarity-based methods: a general framework for classification, approximation and association Control and Cybernetics. ,vol. 29, pp. 937- 967 ,(2000)
Włodzisław Duch, Marcin Blachnik, Fuzzy Rule-Based Systems Derived from Similarity to Prototypes international conference on neural information processing. pp. 912- 917 ,(2004) , 10.1007/978-3-540-30499-9_140
Marcin Blachnik, Włodzisław Duch, Tadeusz Wieczorek, Selection of Prototype Rules: Context Searching Via Clustering Artificial Intelligence and Soft Computing – ICAISC 2006. pp. 573- 582 ,(2006) , 10.1007/11785231_60
Huan Liu, Lei Yu, Feature selection for high-dimensional data: a fast correlation-based filter solution international conference on machine learning. pp. 856- 863 ,(2003)
Rudy Setiono, Huan Liu, Improving backpropagation learning with feature selection Applied Intelligence. ,vol. 6, pp. 129- 139 ,(1996) , 10.1007/BF00117813
Claude E. Shannon, Warren Weaver, Norbert Wiener, The Mathematical Theory of Communication Physics Today. ,vol. 3, pp. 31- 32 ,(1950) , 10.1063/1.3067010
Dasaratha V. Sridhar, Eric B. Bartlett, Richard C. Seagrave, Information theoretic subset selection for neural network models Computers & Chemical Engineering. ,vol. 22, pp. 613- 626 ,(1998) , 10.1016/S0098-1354(97)00227-5
Jacek Biesiada, Włodzisław Duch, Feature Selection for High-Dimensional Data: A Kolmogorov-Smirnov Correlation-Based Filter computer recognition systems. pp. 95- 103 ,(2005) , 10.1007/3-540-32390-2_9
R. López De Mántaras, A Distance-Based Attribute Selection Measure for Decision Tree Induction Machine Learning. ,vol. 6, pp. 81- 92 ,(1991) , 10.1023/A:1022694001379