| Comparative evaluation of approaches to propositionalization MA Krogel, S Rawles, F Železný, PA Flach, N Lavrač, S Wrobel Inductive Logic Programming: 13th International Conference, ILP 2003, Szeged …, 2003 | 184 | 2003 |
| Propositionalization-based relational subgroup discovery with RSD F Železný, N Lavrač Machine Learning 62, 33-63, 2006 | 147 | 2006 |
| RSD: Relational subgroup discovery through first-order feature construction N Lavrac, F Zelezný, PA Flach ILP 2, 149-165, 2002 | 103 | 2002 |
| Automating knowledge discovery workflow composition through ontology-based planning M Žáková, P Křemen, F Železný, N Lavrač IEEE Transactions on Automation Science and Engineering 8 (2), 253-264, 2010 | 102 | 2010 |
| Lifted relational neural networks: Efficient learning of latent relational structures G Sourek, V Aschenbrenner, F Zelezny, S Schockaert, O Kuzelka Journal of Artificial Intelligence Research 62, 69-100, 2018 | 80 | 2018 |
| Induction of comprehensible models for gene expression datasets by subgroup discovery methodology D Gamberger, N Lavrač, F Železný, J Tolar Journal of biomedical informatics 37 (4), 269-284, 2004 | 73 | 2004 |
| Lattice-search runtime distributions may be heavy-tailed F Železný, A Srinivasan, D Page Inductive Logic Programming: 12th International Conference, ILP 2002 Sydney …, 2003 | 72 | 2003 |
| Lifted relational neural networks G Sourek, V Aschenbrenner, F Zelezny, O Kuzelka arXiv preprint arXiv:1508.05128, 2015 | 71 | 2015 |
| Learning to predict soccer results from relational data with gradient boosted trees O Hubáček, G Šourek, F Železný Machine Learning 108, 29-47, 2019 | 57 | 2019 |
| Learning relational descriptions of differentially expressed gene groups I Trajkovski, F Zelezny, N Lavrac, J Tolar IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2007 | 50 | 2007 |
| Block-wise construction of tree-like relational features with monotone reducibility and redundancy O Kuželka, F Železný Machine Learning 83, 163-192, 2011 | 43 | 2011 |
| Exploiting sports-betting market using machine learning O Hubáček, G Šourek, F Železný International Journal of Forecasting 35 (2), 783-796, 2019 | 41 | 2019 |
| Randomised restarted search in ILP F Železný, A Srinivasan, CD Page Machine Learning 64, 183-208, 2006 | 35 | 2006 |
| Sequential data mining: A comparative case study in development of atherosclerosis risk factors J Klema, L Nováková, F Karel, O Stepankova, F Zelezny IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2007 | 34 | 2007 |
| A restarted strategy for efficient subsumption testing O Kuželka, F Železný Fundamenta Informaticae 89 (1), 95-109, 2008 | 33 | 2008 |
| Relational data mining applied to virtual engineering of product designs M Záková, F Zelezny, JA Garcia-Sedano, CM Tissot, N Lavrac, P Kremen, ... Lecture Notes in Computer Science 4455, 439, 2007 | 32 | 2007 |
| Planning to learn with a knowledge discovery ontology M Zakova, P Kremen, F Zelezný, N Lavrac Planning to Learn Workshop (PlanLearn 2008) at ICML 2008, 2008 | 28 | 2008 |
| An experimental test of Occam's razor in classification J Zahálka, F Elezný Machine Learning 82 (3), 475, 2011 | 27 | 2011 |
| Advancing data mining workflow construction: A framework and cases using the orange toolkit M Záková, V Podpecan, F Zelezný, N Lavrac Proc. 2nd Intl. Wshop. Third Generation Data Mining: Towards Service …, 2009 | 26 | 2009 |
| Comparative evaluation of set-level techniques in predictive classification of gene expression samples M Holec, J Kléma, F Železný, J Tolar BMC bioinformatics 13 (10), 1-15, 2012 | 25 | 2012 |
