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Issue Date	Title	Author(s)
Feb-1996	Dimensionality reduction via discretization	Liu, H. ; Setiono, R.
2012	Discrete variable generation for improved neural network classification	Setiono, R. ; Seret, A.
1996	Effective data mining using neural networks	Lu, H. ; Setiono, R. ; Liu, H.
2005	Effective neural network pruning using cross-validation	Huynh, T.Q.; Setiono, R.
2002	Effective query size estimation using neural networks	Lu, H. ; Setiono, R.
1993	Efficient neural network training algorithm for the Cray Y-MP supercomputer	Leung, Chung Siu ; Setiono, Rudy
1999	Explanation of the 'virtual input' phenomenon	Leow, W.K. ; Setiono, R.
2000	Extracting M-of-N rules from trained neural networks	Setiono, R.
1-Jan-1997	Extracting rules from neural networks by pruning and hidden-unit splitting	Setiono, R.
Feb-1996	Extracting rules from pruned neural networks for breast cancer diagnosis	Setiono, R.
2005	Extracting salient dimensions for automatic SOM labeling	Azcarraga, A.P.; Hsieh, M.-H.; Pan, S.L. ; Setiono, R.
2002	Extraction of rules from artificial neural networks for nonlinear regression	Setiono, R. ; Leow, W.K. ; Zurada, J.M.
1997	Feature selection via discretization	Liu, H. ; Setiono, R.
2001	Feedforward neural network construction using cross validation	Setiono, R.
2000	FERNN: an algorithm for fast extraction of rules from neural networks	Setiono, R. ; Leow, W.K.
1998	Fragmentation problem and automated feature construction	Setiono, Rudy ; Liu, Huan
2005	From knowledge discovery to implementation: A business intelligence approach using neural network rule extraction and decision tables	Mues, C.; Baesens, B.; Setiono, R. ; Vanthienen, J.
2000	Generating concise and accurate classification rules for breast cancer diagnosis	Setiono, R.
1999	Generating rules from trained network using fast pruning	Setiono, Rudy ; Leow, Wee Kheng
2008	Greedy rule generation from discrete data and its use in neural network rule extraction	Odajima, K.; Hayashi, Y.; Tianxia, G.; Setiono, R.

Showing results 17 to 36 of 75 < previous next >