R. Setiono

Rudy Setiono, Arnulfo P. Azcarraga, R. Setiono, 2001, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2001.

Incremental Feature Selection

Huan Liu, Rudy Setiono, R. Setiono, 1998, Applied Intelligence.

Computational intelligence methods for rule-based data understanding

Jacek M. Zurada, Wlodzislaw Duch, Rudy Setiono, 2004, Proceedings of the IEEE.

Some issues on scalable feature selection

Huan Liu, Rudy Setiono, R. Setiono, 1998 .

Feature Selection: An Ever Evolving Frontier in Data Mining

Huan Liu, Hiroshi Motoda, Rudy Setiono, 2010, FSDM.

A Probabilistic Approach to Feature Selection - A Filter Solution

Huan Liu, Rudy Setiono, R. Setiono, 1996, ICML.

Generating concise and accurate classification rules for breast cancer diagnosis

Rudy Setiono, R. Setiono, 2000, Artif. Intell. Medicine.

A comparison between two neural network rule extraction techniques for the diagnosis of hepatobiliary disorders

Katsumi Yoshida, Yoichi Hayashi, Rudy Setiono, 2000, Artif. Intell. Medicine.

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

Bart Baesens, Jan Vanthienen, Rudy Setiono, 2003, Manag. Sci..

Extraction of rules from artificial neural networks for nonlinear regression

Jacek M. Zurada, Wee Kheng Leow, Rudy Setiono, 2002, IEEE Trans. Neural Networks.

Feature Transformation and Multivariate Decision Tree Induction

Huan Liu, Rudy Setiono, R. Setiono, 1998, Discovery Science.

Symbolic Representation of Neural Networks

Huan Liu, Rudy Setiono, R. Setiono, 1996, Computer.

Recursive Neural Network Rule Extraction for Data With Mixed Attributes

Bart Baesens, Rudy Setiono, Christophe Mues, 2008, IEEE Transactions on Neural Networks.

An Approach To Generate Rules From Neural Networks for Regression Problems

Rudy Setiono, James Y. L. Thong, R. Setiono, 2004, Eur. J. Oper. Res..

Symbolic Rule Extraction From Neural Networks: An Application to Identifying Organizations Adopting IT

Rudy Setiono, Chee-Sing Yap, James Y. L. Thong, 1998, Inf. Manag..

Extracting rules from pruned networks for breast cancer diagnosis

Rudy Setiono, R. Setiono, 1996, Artif. Intell. Medicine.

FERNN: An Algorithm for Fast Extraction of Rules from Neural Networks

Wee Kheng Leow, Rudy Setiono, W. Leow, 2004, Applied Intelligence.

Feedforward Neural Network Construction Using Cross Validation

Rudy Setiono, R. Setiono, 2001, Neural Computation.

Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring

Bart Baesens, Jan Vanthienen, Rudy Setiono, 2008, Rule Extraction from Support Vector Machines.

Input selection in data-driven fuzzy modeling

Jacek M. Zurada, Rudy Setiono, Adam E. Gaweda, 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

NeuroLinear: From neural networks to oblique decision rules

Huan Liu, Rudy Setiono, R. Setiono, 1997, Neurocomputing.

NeuroLinear: A System for Extracting Oblique Decision Rules from Neural Networks

Huan Liu, Rudy Setiono, R. Setiono, 1997, ECML.

NeuroRule: A Connectionist Approach to Data Mining

Hongjun Lu, Huan Liu, Rudy Setiono, 1995, VLDB.

Minerva: Sequential Covering for Rule Extraction

Bart Baesens, Jan Vanthienen, Rudy Setiono, 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Greedy rule generation from discrete data and its use in neural network rule extraction

Yoichi Hayashi, Rudy Setiono, Koichi Odajima, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

A Penalty-Function Approach for Pruning Feedforward Neural Networks

Rudy Setiono, R. Setiono, 1997, Neural Computation.

Use of a quasi-Newton method in a feedforward neural network construction algorithm

Rudy Setiono, Lucas Chi Kwong Hui, R. Setiono, 1995, IEEE Trans. Neural Networks.

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

Shan Ling Pan, Rudy Setiono, Ming-Huei Hsieh, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Generating Linear Regression Rules from Neural Networks Using Local Least Squares Approximation

Rudy Setiono, R. Setiono, 2001, IWANN.

Feature Selection and Classification - A Probabilistic Wrapper Approach

Huan Liu, Rudy Setiono, R. Setiono, 1996, IEA/AIE.

A Hybrid Connectionist for Multiple Regression

Jacek M. Zurada, Rudy Setiono, R. Setiono, 2003 .

Keyword extraction using backpropagation neural networks and rule extraction

Rudy Setiono, Arnulfo P. Azcarraga, Michael David Liu, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Rule Extraction from Minimal Neural Networks for Credit Card Screening

Bart Baesens, Rudy Setiono, Christophe Mues, 2011, Int. J. Neural Syst..

Building Credit-Risk Evaluation Expert Systems Using Neural Network Rule Extraction and Decision Tables

Bart Baesens, Jan Vanthienen, Stijn Viaene, 2001, ICIS.

Software Effort Prediction Using Regression Rule Extraction from Neural Networks

Bart Baesens, Rudy Setiono, Wouter Verbeke, 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

A note on knowledge discovery using neural networks and its application to credit card screening

Rudy Setiono, Bart Baesens, Christophe Mues, 2009, Eur. J. Oper. Res..

A hybrid SOM-SVM method for analyzing zebra fish gene expression

Wu Wei, Xu Min, Rudy Setiono, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Neural network rule extraction for gaining insight into the characteristics of poverty

R. Setiono, A. Azcarraga, 2018, Neural Computing and Applications.

On the solution of the parity problem by a single hidden layer feedforward neural network

Rudy Setiono, R. Setiono, 1997, Neurocomputing.

Rule Extraction from Neural Networks and Support Vector Machines for Credit Scoring

Bart Baesens, Rudy Setiono, David Martens, 2011 .

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

Yoichi Hayashi, Rudy Setiono, Ming-Huei Hsieh, 2009, J. Oper. Res. Soc..

Improving backpropagation learning with feature selection

Huan Liu, Rudy Setiono, R. Setiono, 1996, Applied Intelligence.

A connectionist approach to generating oblique decision trees

Huan Liu, Rudy Setiono, R. Setiono, 1999, IEEE Trans. Syst. Man Cybern. Part B.

Fragmentation problem and automated feature construction

Huan Liu, Rudy Setiono, R. Setiono, 1998, Proceedings Tenth IEEE International Conference on Tools with Artificial Intelligence (Cat. No.98CH36294).

Feature extraction via Neural networks

Huan Liu, Rudy Setiono, R. Setiono, 1998 .

Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring

B. Baesens, R. Setiono, J. Vanthienen, 2008, Rule Extraction from Support Vector Machines.

Pruned Neural Networks for Regression

Wee Kheng Leow, Rudy Setiono, W. Leow, 2000, PRICAI.

Knowledge acquisition and revision via neural networks

R. Setiono, A. Azcarraga, M. Hsieh, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

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

Shan Ling Pan, Rudy Setiono, Ming-Huei Hsieh, 2006, J. Oper. Res. Soc..

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

Rudy Setiono, R. Setiono, 1997, Neural Computation.

Program Committee ICSIIT 2017

Anastasia Rita Widiarti, Cherry G. Ballangan, Kassim S. Mwitondi, 2017 .

Risk Management and Regulatory Compliance: A Data Mining Framework Based on Neural Network Rule Extraction

Bart Baesens, Rudy Setiono, Christophe Mues, 2006, ICIS.