| Exceptional model mining D Leman, A Feelders, A Knobbe Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008 | 199 | 2008 |
| Exceptional Model Mining: Supervised descriptive local pattern mining with complex target concepts W Duivesteijn, AJ Feelders, A Knobbe Data Mining and Knowledge Discovery 30, 47-98, 2016 | 179 | 2016 |
| Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review FR Goes, LA Meerhoff, MJO Bueno, DM Rodrigues, FA Moura, MS Brink, ... European Journal of Sport Science 21 (4), 481-496, 2021 | 171 | 2021 |
| Diverse subgroup set discovery M Van Leeuwen, A Knobbe Data Mining and Knowledge Discovery 25, 208-242, 2012 | 170 | 2012 |
| Propositionalisation and aggregates AJ Knobbe, M De Haas, A Siebes European Conference on Principles of Data Mining and Knowledge Discovery …, 2001 | 152 | 2001 |
| Pattern teams AJ Knobbe, EKY Ho European Conference on Principles of Data Mining and Knowledge Discovery …, 2006 | 129 | 2006 |
| Social competence at the playground: Preschoolers during recess G Veiga, W De Leng, R Cachucho, L Ketelaar, JN Kok, A Knobbe, C Neto, ... Infant and Child Development 26 (1), e1957, 2017 | 124 | 2017 |
| From local patterns to global models: the LeGo approach to data mining A Knobbe, B Crémilleux, J Fürnkranz, M Scholz From local patterns to global models: Proceedings of the ECML/PKDD-08 …, 2008 | 124 | 2008 |
| Football Player's Performance and Market Value. M He, R Cachucho, AJ Knobbe Mlsa@ pkdd/ecml, 87-95, 2015 | 112 | 2015 |
| System and method for generating performance models of complex information technology systems PW Adriaans, AJ Knobbe, M Gathier US Patent 6,311,175, 2001 | 107 | 2001 |
| A defect classification methodology for sewer image sets with convolutional neural networks D Meijer, L Scholten, F Clemens, A Knobbe Automation in Construction 104, 281-298, 2019 | 98 | 2019 |
| Multi-relational data mining BLJ Kaczmarek, AJ Knobbe Ios Press, 2006 | 98 | 2006 |
| Multi-relational data mining AJ Knobbe, H Blockeel, A Siebes, DMG Van der Wallen Centrum voor wiskunde en informatica, 1999 | 97 | 1999 |
| Subgroup discovery meets bayesian networks--an exceptional model mining approach W Duivesteijn, A Knobbe, A Feelders, M van Leeuwen 2010 IEEE International Conference on Data Mining, 158-167, 2010 | 84 | 2010 |
| Maximally informative k-itemsets and their efficient discovery AJ Knobbe, EKY Ho Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 81 | 2006 |
| Exploiting false discoveries--statistical validation of patterns and quality measures in subgroup discovery W Duivesteijn, A Knobbe 2011 IEEE 11th International Conference on Data Mining, 151-160, 2011 | 78 | 2011 |
| Multi-relational decision tree induction AJ Knobbe, A Siebes, D van der Wallen Principles of Data Mining and Knowledge Discovery: Third European Conference …, 1999 | 73 | 1999 |
| Benefits of a short, practical questionnaire to measure subjective perception of nasal appearance after aesthetic rhinoplasty PJFM Lohuis, S Hakim, W Duivesteijn, A Knobbe, AJ Tasman Plastic and reconstructive surgery 132 (6), 913e-923e, 2013 | 69 | 2013 |
| Personalized machine learning approach to injury monitoring in elite volleyball players AW de Leeuw, S van der Zwaard, R van Baar, A Knobbe European journal of sport science 22 (4), 511-520, 2022 | 67 | 2022 |
| Entropy-based discretization methods for ranking data CR De Sá, C Soares, A Knobbe Information Sciences 329, 921-936, 2016 | 65 | 2016 |
Wouter DuivesteijnTU EindhovenVerified email at tue.nl