| Chi2: Feature selection and discretization of numeric attributes H Liu, R Setiono Proceedings of 7th IEEE international conference on tools with artificial …, 1995 | 1477 | 1995 |
| A probabilistic approach to feature selection-a filter solution H Liu, R Setiono ICML 96, 319-327, 1996 | 1112 | 1996 |
| Product-, corporate-, and country-image dimensions and purchase behavior: A multicountry analysis MH Hsieh, SL Pan, R Setiono Journal of the Academy of marketing Science 32 (3), 251-270, 2004 | 951 | 2004 |
| Using neural network rule extraction and decision tables for credit-risk evaluation B Baesens, R Setiono, C Mues, J Vanthienen Management science 49 (3), 312-329, 2003 | 739 | 2003 |
| Effective data mining using neural networks H Lu, R Setiono, H Liu IEEE transactions on knowledge and data engineering 8 (6), 957-961, 1996 | 642 | 1996 |
| Feature selection: An ever evolving frontier in data mining H Liu, H Motoda, R Setiono, Z Zhao Feature selection in data mining, 4-13, 2010 | 591 | 2010 |
| Neural-network feature selector R Setiono, H Liu IEEE transactions on neural networks 8 (3), 654-662, 1997 | 559 | 1997 |
| Feature selection via discretization H Liu, R Setiono IEEE Transactions on knowledge and Data Engineering 9 (4), 642-645, 1997 | 506 | 1997 |
| Pattern recognition via linear programming: theory and applications to medical diagnosis OL Mangasarian Large-scale numerical optimization, 22-30, 1990 | 445 | 1990 |
| Generating concise and accurate classification rules for breast cancer diagnosis R Setiono Artificial Intelligence in medicine 18 (3), 205-219, 2000 | 355 | 2000 |
| Computational intelligence methods for rule-based data understanding W Duch, R Setiono, JM Zurada Proceedings of the IEEE 92 (5), 771-805, 2004 | 289 | 2004 |
| Use of a quasi-Newton method in a feedforward neural network construction algorithm R Setiono, LCK Hui IEEE Transactions on Neural Networks 6 (1), 273-277, 1995 | 289 | 1995 |
| Symbolic representation of neural networks R Setiono, H Liu Computer 29 (3), 71-77, 1996 | 280 | 1996 |
| A penalty-function approach for pruning feedforward neural networks R Setiono Neural computation 9 (1), 185-204, 1997 | 277 | 1997 |
| Extraction of rules from artificial neural networks for nonlinear regression R Setiono, WK Leow, JM Zurada IEEE transactions on neural networks 13 (3), 564-577, 2002 | 276 | 2002 |
| Incremental feature selection H Liu, R Setiono Applied Intelligence 9, 217-230, 1998 | 265 | 1998 |
| Extracting rules from neural networks by pruning and hidden-unit splitting R Setiono Neural Computation 9 (1), 205-225, 1997 | 243 | 1997 |
| Feature selection and classification–a probabilistic wrapper approach H Liu, R Setiono Industrial and engineering applications or artificial intelligence and …, 2022 | 235 | 2022 |
| Understanding neural networks via rule extraction R Setiono, H Liu IJCAI 1, 480-485, 1995 | 229 | 1995 |
| Neurorule: A connectionist approach to data mining H Lu, R Setiono, H Liu arXiv preprint arXiv:1701.01358, 2017 | 227 | 2017 |
