| Web mining research: A survey R Kosala, H Blockeel ACM Sigkdd Explorations Newsletter 2 (1), 1-15, 2000 | 2590 | 2000 |
| Top-down induction of first-order logical decision trees H Blockeel, L De Raedt Artificial intelligence 101 (1-2), 285-297, 1998 | 1101 | 1998 |
| Decision trees for hierarchical multi-label classification C Vens, J Struyf, L Schietgat, S Džeroski, H Blockeel Machine learning 73, 185-214, 2008 | 874 | 2008 |
| Top-down induction of clustering trees H Blockeel, L De Raedt, J Ramon arXiv preprint cs/0011032, 2000 | 691 | 2000 |
| Predicting gene function using hierarchical multi-label decision tree ensembles L Schietgat, C Vens, J Struyf, H Blockeel, D Kocev, S Džeroski BMC bioinformatics 11, 1-14, 2010 | 240 | 2010 |
| Efficient algorithms for decision tree cross-validation H Blockeel, J Struyf Journal of Machine Learning Research 3 (Dec), 621-650, 2002 | 235 | 2002 |
| Decision trees for hierarchical multilabel classification: A case study in functional genomics H Blockeel, L Schietgat, J Struyf, S Džeroski, A Clare Knowledge Discovery in Databases: PKDD 2006: 10th European Conference on …, 2006 | 196 | 2006 |
| On estimating model accuracy with repeated cross-validation G Vanwinckelen, H Blockeel BeneLearn 2012: Proceedings of the 21st Belgian-Dutch conference on machine …, 2012 | 182 | 2012 |
| Scaling up inductive logic programming by learning from interpretations H Blockeel, L De Raedt, N Jacobs, B Demoen Data Mining and Knowledge Discovery 3, 59-93, 1999 | 170 | 1999 |
| Improving the efficiency of inductive logic programming through the use of query packs H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... Journal of Artificial Intelligence Research 16, 135-166, 2002 | 161 | 2002 |
| Hierarchical multi-classification H Blockeel, M Bruynooghe, S Džeroski, J Ramon, J Struyf Workshop notes of the kdd'02 workshop on multi-relational data mining, 21-35, 2002 | 142 | 2002 |
| Experiment databases: A new way to share, organize and learn from experiments J Vanschoren, H Blockeel, B Pfahringer, G Holmes Machine Learning 87, 127-158, 2012 | 141 | 2012 |
| Relational reinforcement learning S Dzeroski, L De Raedt, H Blockeel Lecture notes in computer science 1446, 11-22, 1998 | 134 | 1998 |
| Mining data from intensive care patients J Ramon, D Fierens, F Güiza, G Meyfroidt, H Blockeel, M Bruynooghe, ... Advanced Engineering Informatics 21 (3), 243-256, 2007 | 122 | 2007 |
| Speeding up relational reinforcement learning through the use of an incremental first order decision tree learner K Driessens, J Ramon, H Blockeel Machine Learning: ECML 2001: 12th European Conference on Machine Learning …, 2001 | 122 | 2001 |
| Multi-instance tree learning H Blockeel, D Page, A Srinivasan Proceedings of the 22nd international conference on Machine learning, 57-64, 2005 | 116 | 2005 |
| Seeing the forest through the trees: Learning a comprehensible model from an ensemble A Van Assche, H Blockeel Machine Learning: ECML 2007: 18th European Conference on Machine Learning …, 2007 | 112 | 2007 |
| Query transformations for improving the efficiency of ILP systems VS Costa, A Srinivasan, R Camacho, H Blockeel, B Demoen, G Janssens, ... Journal of Machine Learning Research 4 (Aug), 465-491, 2003 | 102 | 2003 |
| Multi-relational data mining A Knobbe, H Blockeel, A Siebes, D van der Wallen Proceedings of the 9th Belgian-Dutch Conference on Machine Learning, 61-74, 1999 | 99 | 1999 |
| Using internal validity measures to compare clustering algorithms T Van Craenendonck, H Blockeel Benelearn 2015 Poster presentations (online), 1-8, 2015 | 92 | 2015 |
