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SETIONO,RUDY
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Showing results 17 to 36 of 75
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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
2006
Greedy rule generation from discrete data and its use in neural network rule extraction
Odajima, K.
;
Hayashi, Y.
;
Setiono, R.