| Ant colony decision trees–a new method for constructing decision trees based on ant colony optimization U Boryczka, J Kozak International Conference on Computational Collective Intelligence, 373-382, 2010 | 69* | 2010 |
| Decision tree and ensemble learning based on ant colony optimization J Kozak Springer International Publishing, 2019 | 62 | 2019 |
| Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management J Kozak, K Kania, P Juszczuk, M Mitręga International journal of information management 60, 102357, 2021 | 46 | 2021 |
| Rapid detection of fake news based on machine learning methods B Probierz, P Stefański, J Kozak Procedia Computer Science 192, 2893-2902, 2021 | 44 | 2021 |
| Enhancing the effectiveness of ant colony decision tree algorithms by co-learning U Boryczka, J Kozak Applied Soft Computing 30, 166-178, 2015 | 36 | 2015 |
| An adaptive discretization in the ACDT algorithm for continuous attributes U Boryczka, J Kozak Computational Collective Intelligence. Technologies and Applications: Third …, 2011 | 35 | 2011 |
| Collective data mining in the ant colony decision tree approach J Kozak, U Boryczka Information Sciences 372, 126-147, 2016 | 32 | 2016 |
| New algorithms for generation decision trees—ant-miner and its modifications U Boryczka, J Kozak Foundations of Computational, IntelligenceVolume 6: Data Mining, 229-262, 2009 | 31 | 2009 |
| Multiple boosting in the ant colony decision forest meta-classifier J Kozak, U Boryczka Knowledge-Based Systems 75, 141-151, 2015 | 29 | 2015 |
| Real-world data difficulty estimation with the use of entropy P Juszczuk, J Kozak, G Dziczkowski, S Głowania, T Jach, B Probierz Entropy 23 (12), 1621, 2021 | 17 | 2021 |
| Using similarity measures in prediction of changes in financial market stream data—Experimental approach P Juszczuk, J Kozak, K Kania Data & Knowledge Engineering 125, 101782, 2020 | 17 | 2020 |
| Preference-driven classification measure J Kozak, B Probierz, K Kania, P Juszczuk Entropy 24 (4), 531, 2022 | 13 | 2022 |
| Heterogeneous ensembles of classifiers in predicting Bundesliga football results J Kozak, S Głowania Procedia Computer Science 192, 1573-1582, 2021 | 13 | 2021 |
| Permutation entropy as a measure of information gain/loss in the different symbolic descriptions of financial data J Kozak, K Kania, P Juszczuk Entropy 22 (3), 330, 2020 | 13 | 2020 |
| Dynamic version of the acdt/acdf algorithm for h-bond data set analysis J Kozak, U Boryczka Computational Collective Intelligence. Technologies and Applications: 5th …, 2013 | 13 | 2013 |
| Clustering of scientific articles using natural language processing B Probierz, J Kozak, A Hrabia Procedia Computer Science 207, 3449-3458, 2022 | 12 | 2022 |
| An ant colony optimization algorithm for an automatic categorization of emails U Boryczka, B Probierz, J Kozak Computational Collective Intelligence. Technologies and Applications: 6th …, 2014 | 12 | 2014 |
| Decision Trees on the Foreign Exchange Market P Juszczuk, J Kozak, K Trynda Intelligent Decision Technologies 2016, 127-138, 2016 | 11* | 2016 |
| Ant colony decision forest meta-ensemble U Boryczka, J Kozak Computational Collective Intelligence. Technologies and Applications: 4th …, 2012 | 11 | 2012 |
| On-the-go adaptability in the new ant colony decision forest approach U Boryczka, J Kozak Intelligent Information and Database Systems: 6th Asian Conference, ACIIDS …, 2014 | 10 | 2014 |
Przemysław JuszczukUniversity of Economics in KatowiceZweryfikowany adres z ue.katowice.pl
