World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
11980
World Ranking
8623
National Ranking
110

Overview

Rudy Setiono is affiliated with the National University of Singapore, based in Singapore. Their research output is concentrated in the field of Computer Science, with a specific focus on subfields such as Artificial Intelligence and Computational Theory and Mathematics.

The scholar's work covers main topics including:

  • Neural Networks and Applications
  • Fuzzy Logic and Control Systems
  • Rough Sets and Fuzzy Logic

Collaborative research efforts include frequent co-authorship with Huan Liu.

Best Publications

  • Chi2: feature selection and discretization of numeric attributes

    Huan Liu;R. Setiono

  • A probabilistic approach to feature selection - a filter solution

    Huan Liu;Rudy Setiono

  • Product-, corporate-, and country-image dimensions and purchase behavior: A multicountry analysis

    Ming-Huei Hsieh;Shan-Ling Pan;Rudy Setiono

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

    Bart Baesens;Rudy Setiono;Christophe Mues;Jan Vanthienen

  • Effective data mining using neural networks

    Hongjun Lu;R. Setiono;Huan Liu

  • Neural-network feature selector

    Rudy Setiono;Huan Liu

  • Feature selection via discretization

    Huan Liu;R. Setiono

  • Feature Selection: An Ever Evolving Frontier in Data Mining

    Huan Liu;Hiroshi Motoda;Rudy Setiono;Zheng Zhao

  • Pattern Recognition Via Linear Programming: Theory and Application to Medical Diagnosis

    William H Wolberg;Olvi L Mangasarian;Rudy Setiono

  • Generating concise and accurate classification rules for breast cancer diagnosis

    Rudy Setiono

  • Computational intelligence methods for rule-based data understanding

    W. Duch;R. Setiono;J.M. Zurada

  • A penalty-function approach for pruning feedforward neural networks

    Rudy Setiono

  • Symbolic representation of neural networks

    R. Setiono;Huan Liu

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

    R. Setiono;L.C.K. Hui

  • Extraction of rules from artificial neural networks for nonlinear regression

    R. Setiono;Wee Kheng Leow;J.M. Zurada

  • Incremental Feature Selection

    Huan Liu;Rudy Setiono

  • Extracting rules from neural networks by pruning and hidden-unit splitting

    Rudy Setiono

  • Extracting rules from pruned neural networks for breast cancer diagnosis

    Rudy Setiono

  • FERNN: An Algorithm for Fast Extraction of Rules fromNeural Networks

    Rudy Setiono;Wee Kheng Leow

  • Understanding neural networks via rule extraction

    Rudy Setiono;Huan Liu

Frequent Co-Authors

Huan Liu
Huan Liu Arizona State University
Bart Baesens
Bart Baesens KU Leuven
Yoichi Hayashi
Yoichi Hayashi Meiji University
David Martens
David Martens University of Antwerp
Shan Ling Pan
Shan Ling Pan University of New South Wales
Jacek M. Zurada
Jacek M. Zurada University of Louisville
Hongjun Lu
Hongjun Lu Hong Kong University of Science and Technology
Hiroshi Motoda
Hiroshi Motoda Osaka University
Guojun Lu
Guojun Lu Federation University Australia

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