Comparative evaluation of approaches to propositionalization MA Krogel, S Rawles, F Železný, PA Flach, N Lavrač, S Wrobel International Conference on Inductive Logic Programming, 197-214, 2003 | 193 | 2003 |
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 | 152 | 2018 |
Propositionalization-based relational subgroup discovery with RSD F Železný, N Lavrač Machine Learning 62, 33-63, 2006 | 150 | 2006 |
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 | 112 | 2010 |
RSD: Relational subgroup discovery through first-order feature construction N Lavrač, F Železný, PA Flach International conference on inductive logic programming, 149-165, 2002 | 103 | 2002 |
Exploiting sports-betting market using machine learning O Hubáček, G Šourek, F Železný International Journal of Forecasting 35 (2), 783-796, 2019 | 87 | 2019 |
Learning to predict soccer results from relational data with gradient boosted trees O Hubáček, G Šourek, F Železný Machine Learning 108, 29-47, 2019 | 79 | 2019 |
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 | 77 | 2004 |
Lattice-search runtime distributions may be heavy-tailed F Železný, A Srinivasan, D Page International conference on inductive logic programming, 333-345, 2002 | 69 | 2002 |
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 | 51 | 2007 |
Block-wise construction of tree-like relational features with monotone reducibility and redundancy O Kuželka, F Železný Machine Learning 83, 163-192, 2011 | 47 | 2011 |
A restarted strategy for efficient subsumption testing O Kuželka, F Železný Fundamenta Informaticae 89 (1), 95-109, 2008 | 37 | 2008 |
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 |
Relational data mining applied to virtual engineering of product designs M Žáková, F Železný, JA Garcia-Sedano, C Masia Tissot, N Lavrač, ... Inductive Logic Programming: 16th International Conference, ILP 2006 …, 2007 | 33 | 2007 |
Lifted relational neural networks G Šourek, V Aschenbrenner, F Zelezný, O Kuzelka Proceedings of the NIPS Workshop on Cognitive Computation: Integrating …, 2015 | 30 | 2015 |
Comparative evaluation of set-level techniques in predictive classification of gene expression samples M Holec, J Kléma, F Železný, J Tolar BMC bioinformatics 13, 1-15, 2012 | 27 | 2012 |
An experimental test of Occam’s razor in classification J Zahálka, F Železný Machine Learning 82, 475-481, 2011 | 27 | 2011 |
Machine learning and knowledge discovery in databases HBK Kersting, SNF Železný Springer, 2013 | 26 | 2013 |
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 |