Bernard Ženko

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Saso DzeroskiJozef Stefan Institute, Dept. of Knowledge TechnologiesVerified email at ijs.si
Ljupco TodorovskiFull Professor, University of Ljubljana, Faculty of Mathematics and PhysicsVerified email at fmf.uni-lj.si
Nada LavracJozef Stefan InstituteVerified email at ijs.si
Timo AhoCloud Data Expert PhDVerified email at tietoevry.com
Alexis MitelpunktTel Aviv University; Tel Aviv Sourasky Medical CenterVerified email at post.tau.ac.il
Aljaž OsojnikResearcher, Jožef Stefan InstituteVerified email at ijs.si
Dragi KocevJožef Stefan InstituteVerified email at ijs.si
Tapio ElomaaVerified email at tut.fi
Nikola SimidjievskiUniversity of Cambridge, United KingdomVerified email at cam.ac.uk
Martin BreskvarJožef Stefan InstituteVerified email at ijs.si
Matej PetkovićJožef Stefan InstituteVerified email at ijs.si
Jurica LevaticPostdoc, Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, SloveniaVerified email at ijs.si
Panče PanovJožef Stefan InstituteVerified email at ijs.si
Tea TušarResearch fellow, Jožef Stefan InstituteVerified email at ijs.si
Domen MongusAssoc. Professor of Computer Science, University of MariborVerified email at um.si
Zoran LevnajićFaculty of information studies, Novo mesto, SloveniaVerified email at fis.unm.si
Marko BohanecJožef Stefan Institute, Ljubljana, SloveniaVerified email at ijs.si
Joao GamaProfessor, Faculty of Economics, University of Porto, and INESC TECVerified email at fep.up.pt
Luis Moreira-MatiasSenior Director of Artificial Intelligence (sennAI) @ sennderVerified email at sennder.com
Jihed KhiariJohannes Kepler University, LinzVerified email at jku.at

Bernard Ženko

Jožef Stefan Institute

Verified email at ijs.si - Homepage

Computer science Artificial intelligence Machine learning Data mining


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Is combining classifiers better than selecting the best one? S Džeroski, B Ženko International Conference on Machine Learning 2002, 123-130, 2002	1073*	2002
Is combining classifiers with stacking better than selecting the best one? S Džeroski, B Ženko Machine learning 54 (3), 255-273, 2004	989	2004
Multi-target regression with rule ensembles T Aho, B Ženko, S Džeroski, T Elomaa Journal of Machine Learning Research 13 (Aug), 2367-2407, 2012	108	2012
Yeasts and yeast-like fungi in tap water and groundwater, and their transmission to household appliances MN Babič, P Zalar, B Ženko, S Džeroski, N Gunde-Cimerman Fungal Ecology 20, 30-39, 2016	80	2016
Candida and Fusarium species known as opportunistic human pathogens from customer-accessible parts of residential washing machines MN Babič, P Zalar, B Ženko, HJ Schroers, S Džeroski, ... Fungal biology 119 (2-3), 95-113, 2015	80	2015
Gut microbiota patterns associated with colonization of different Clostridium difficile ribotypes J Škraban, S Džeroski, B Ženko, D Mongus, S Gangl, M Rupnik PloS one 8 (2), e58005, 2013	76	2013
Learning predictive clustering rules B Ženko, S Džeroski, J Struyf International Workshop on Knowledge Discovery in Inductive Databases 3933 …, 2005	76	2005
A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods B Ženko, L Todorovski, S Džeroski IEEE International Conference on Data Mining, 669-670, 2001	62	2001
Stacking with multi-response model trees S Džeroski, B Ženko International workshop on multiple classifier systems 2364, 201-211, 2002	57	2002
Speeding-up hoeffding-based regression trees with options E Ikonomovska, J Gama, B Ženko, S Džeroski International Conference on Machine Learning, 537-544, 2011	50	2011
Personality traits in miners with past occupational elemental mercury exposure DK Grum, AB Kobal, N Arnerič, M Horvat, B Ženko, S Džeroski, J Osredkar Environmental health perspectives 114 (2), 290-296, 2006	50	2006
Neuroblastoma tumorigenesis is regulated through the Nm23-H1/h-Prune C-terminal interaction M Carotenuto, E Pedone, D Diana, P De Antonellis, S Džeroski, N Marino, ... Scientific reports 3 (1351), 1-11, 2013	40	2013
Estimating the risk of fire outbreaks in the natural environment D Stojanova, A Kobler, P Ogrinc, B Ženko, S Džeroski Data mining and knowledge discovery 24 (2), 411-442, 2012	40	2012
Ensemble methods in machine learning S Džeroski, P Panov, B Ženko Encyclopedia of Complexity and Systems Science 6, 5317-5325, 2009	38*	2009
A study of overfitting in optimization of a manufacturing quality control procedure T Tušar, K Gantar, V Koblar, B Ženko, B Filipič Applied Soft Computing 59, 77-87, 2017	36	2017
Rule ensembles for multi-target regression T Aho, B Ženko, S Džeroski IEEE International Conference on Data Mining, 21-30, 2009	29	2009
Clusters of male and female Alzheimer’s disease patients in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database D Gamberger, B Ženko, A Mitelpunkt, N Shachar, N Lavrač Brain informatics 3 (3), 169, 2016	27	2016
Learning classification rules for multiple target attributes B Ženko, S Džeroski Pacific-Asia Conference on Knowledge Discovery and Data Mining 5012, 454-465, 2008	27	2008
Changes of poultry faecal microbiota associated with Clostridium difficile colonisation J Škraban, S Džeroski, B Ženko, L Tušar, M Rupnik Veterinary microbiology 165 (3-4), 416-424, 2013	25	2013
Evaluation method for feature rankings and their aggregations for biomarker discovery I Slavkov, B Ženko, S Džeroski Machine Learning in Systems Biology, 122-135, 2009	22	2009

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