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Recursive Neural Network Rule Extraction for Data With Mixed Attributes

IEEE transaction on neural networks and learning systems, 2008-02, Vol.19 (2), p.299-307

2008

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Computational intelligence methods for rule-based data understanding

Proceedings of the IEEE, 2004-05, Vol.92 (5), p.771-805

2004

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Extraction of rules from artificial neural networks for nonlinear regression

IEEE transaction on neural networks and learning systems, 2002-05, Vol.13 (3), p.564-577

2002

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Extracting M-of-N rules from trained neural networks

IEEE transaction on neural networks and learning systems, 2000-03, Vol.11 (2), p.512-519

Setiono, R.

2000

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Feature selection via discretization

IEEE transactions on knowledge and data engineering, 1997-07, Vol.9 (4), p.642-645

1997

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Effective data mining using neural networks

IEEE transactions on knowledge and data engineering, 1996-12, Vol.8 (6), p.957-961

1996

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Symbolic representation of neural networks

Computer (Long Beach, Calif.), 1996-03, Vol.29 (3), p.71-77

1996

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Predicting consumer preference for fast-food franchises: a data mining approach

The Journal of the Operational Research Society, 2009-09, Vol.60 (9), p.1221-1229

2009

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Generating concise and accurate classification rules for breast cancer diagnosis

Artificial intelligence in medicine, 2000-03, Vol.18 (3), p.205-219

Setiono, Rudy

2000

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Minerva: Sequential Covering for Rule Extraction

IEEE transactions on cybernetics, 2008-04, Vol.38 (2), p.299-309

2008

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Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation

Management science, 2003-03, Vol.49 (3), p.312-329

2003

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Feedforward Neural Network Construction Using Cross Validation

Neural computation, 2001-12, Vol.13 (12), p.2865-2877

Setiono, Rudy

2001

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Product-, Corporate-, and Country-Image Dimensions and Purchase Behavior: A Multicountry Analysis

Journal of the Academy of Marketing Science, 2004-06, Vol.32 (3), p.251-270

2004

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Extracting salient dimensions for automatic SOM labeling

IEEE transactions on human-machine systems, 2005-11, Vol.35 (4), p.595-600

2005

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Automatic knowledge extraction from survey data: learning M-of-N constructs using a hybrid approach

The Journal of the Operational Research Society, 2005-01, Vol.56 (1), p.3-14

2005

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Knowledge acquisition and revision using neural networks: an application to a cross-national study of brand image perception

The Journal of the Operational Research Society, 2006-03, Vol.57 (3), p.231-240

2006

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A Penalty-Function Approach for Pruning Feedforward Neural Networks

Neural computation, 1997-01, Vol.9 (1), p.185-204

Setiono, Rudy

1997

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Rule extraction from minimal neural networks for credit card screening

International journal of neural systems, 2011-08, Vol.21 (4), p.265-276

2011

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Separating core and noncore knowledge: an application of neural network rule extraction to a cross-national study of brand image perception

IEEE transactions on human-machine systems, 2005-11, Vol.35 (4), p.465-475

2005

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Extracting Rules from Neural Networks by Pruning and Hidden-Unit Splitting

Neural computation, 1997-01, Vol.9 (1), p.205-225

Setiono, Rudy

1997

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On mapping decision trees and neural networks

Knowledge-based systems, 1999-06, Vol.12 (3), p.95-99

1999

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Incremental Feature Selection

Applied intelligence (Dordrecht, Netherlands), 1998-11, Vol.9 (3), p.217-230

1998

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A comparative study of centroid-based, neighborhood-based and statistical approaches for effective document categorization

Object recognition supported by user interaction for service robots, 2002, Vol.4, p.235-238 vol.4

2002

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Interior proximal point algorithm for linear programs

Journal of optimization theory and applications, 1992-09, Vol.74 (3), p.425-444

SETIONO, R

1992

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An approach to generate rules from neural networks for regression problems

European journal of operational research, 2004-05, Vol.155 (1), p.239-250

2004

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Recursive Neural Network Rule Extraction for Data With Mixed Attributes

Computational intelligence methods for rule-based data understanding

Extraction of rules from artificial neural networks for nonlinear regression

Extracting M-of-N rules from trained neural networks

Feature selection via discretization

Effective data mining using neural networks

Symbolic representation of neural networks

Predicting consumer preference for fast-food franchises: a data mining approach

Generating concise and accurate classification rules for breast cancer diagnosis

Minerva: Sequential Covering for Rule Extraction

Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation

Feedforward Neural Network Construction Using Cross Validation

Product-, Corporate-, and Country-Image Dimensions and Purchase Behavior: A Multicountry Analysis

Extracting salient dimensions for automatic SOM labeling

Automatic knowledge extraction from survey data: learning M-of-N constructs using a hybrid approach

Knowledge acquisition and revision using neural networks: an application to a cross-national study of brand image perception

A Penalty-Function Approach for Pruning Feedforward Neural Networks

Rule extraction from minimal neural networks for credit card screening

Separating core and noncore knowledge: an application of neural network rule extraction to a cross-national study of brand image perception

Extracting Rules from Neural Networks by Pruning and Hidden-Unit Splitting

On mapping decision trees and neural networks

Incremental Feature Selection

A comparative study of centroid-based, neighborhood-based and statistical approaches for effective document categorization

Interior proximal point algorithm for linear programs

An approach to generate rules from neural networks for regression problems

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