Mykola Pechenizkiy - Google Scholar

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Citations	7735	5411
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Co-authors

Alexey TsymbalSiemens AGVerified email at siemens.com
Indrė ŽliobaitėUniversity of HelsinkiVerified email at helsinki.fi
Paul De BraProfessor of Computer Science, Eindhoven University of TechnologyVerified email at win.tue.nl
Toon CaldersUniversity of AntwerpVerified email at uantwerpen.be
Joao GamaProfessor, Faculty of Economics, University of PortoVerified email at fep.up.pt
Sebastián VenturaProfessor of Computer Science and Artificial Intelligence, University of CordobaVerified email at uco.es
Cristobal RomeroFull Professor in University of Cordoba and member of KDIS Research GroupVerified email at uco.es
George H. L. FletcherEindhoven University of TechnologyVerified email at tue.nl
Padraig CunninghamProfessor of Knowledge and Data Engineering, University College DublinVerified email at ucd.ie
Evgeny KnutovKnowSyms B.V.Verified email at knowsyms.com
Jorn BakkerPhD Candidate, Eindhoven University of TechnologyVerified email at tue.nl
Pei YulongEindhoven University of TechnologyVerified email at tue.nl
Wil van der AalstProfessor of Process and Data Science, RWTH Aachen University || Fraunhofer FIT || TU/e || TiUVerified email at pads.rwth-aachen.de
Ryan BakerUniversity of PennsylvaniaVerified email at upenn.edu
Paolo SodaAssistant professor of Computer Science and Computer Engineering, Università Campus Bio-Medico di RomaVerified email at unicampus.it
Faisal KamiranInformation Technology University of The PunjabVerified email at itu.edu.pk
Albert BifetTélécom ParisTech & University of WaikatoVerified email at telecom-paristech.fr
Natalia SidorovaTechnische Universiteit EindhovenVerified email at tue.nl
Alexandr MaslovEindhoven University of TechnologyVerified email at tue.nl
R. P. Jagadeesh Chandra BoseDepartment of Mathematics and Computer Science, Eindhoven University of Technology, The NetherlandsVerified email at tue.nl

Mykola Pechenizkiy

Eindhoven University of Technology

Verified email at tue.nl - Homepage

data mining predictive analytics fairness transparency accountability


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A survey on concept drift adaptation J Gama, I Žliobaitė, A Bifet, M Pechenizkiy, A Bouchachia ACM computing surveys (CSUR) 46 (4), 1-37, 2014	1426	2014
Predicting Students Drop Out: A Case Study. GW Dekker, M Pechenizkiy, JM Vleeshouwers International Working Group on Educational Data Mining, 2009	463	2009
Handbook of educational data mining C Romero, S Ventura, M Pechenizkiy, RSJ Baker CRC press, 2010	438	2010
Diversity in search strategies for ensemble feature selection A Tsymbal, M Pechenizkiy, P Cunningham Information fusion 6 (1), 83-98, 2005	320	2005
AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques E Knutov, P De Bra, M Pechenizkiy New review of hypermedia and multimedia 15 (1), 5-38, 2009	246	2009
Dynamic integration of classifiers for handling concept drift A Tsymbal, M Pechenizkiy, P Cunningham, S Puuronen Information fusion 9 (1), 56-68, 2008	224	2008
What's your current stress level? Detection of stress patterns from GSR sensor data J Bakker, M Pechenizkiy, N Sidorova 2011 IEEE 11th international conference on data mining workshops, 573-580, 2011	208	2011
Discrimination aware decision tree learning F Kamiran, T Calders, M Pechenizkiy 2010 IEEE International Conference on Data Mining, 869-874, 2010	208	2010
Handling concept drift in process mining RPJC Bose, WMP van der Aalst, I Žliobaitė, M Pechenizkiy International Conference on Advanced Information Systems Engineering, 391-405, 2011	181	2011
Building classifiers with independency constraints T Calders, F Kamiran, M Pechenizkiy 2009 IEEE International Conference on Data Mining Workshops, 13-18, 2009	176	2009
An overview of concept drift applications I Žliobaitė, M Pechenizkiy, J Gama Big data analysis: new algorithms for a new society, 91-114, 2016	164	2016
Stress detection from speech and galvanic skin response signals H Kurniawan, AV Maslov, M Pechenizkiy Proceedings of the 26th IEEE International Symposium on Computer-Based …, 2013	149	2013
A response time model for bottom-out hints as worked examples B Shih, KR Koedinger, R Scheines Handbook of educational data mining, 201-212, 2011	135	2011
Graph-based n-gram language identification on short texts E Tromp, M Pechenizkiy Proc. 20th Machine Learning conference of Belgium and The Netherlands, 27-34, 2011	130	2011
Dealing with concept drifts in process mining RPJC Bose, WMP Van Der Aalst, I Žliobaitė, M Pechenizkiy IEEE transactions on neural networks and learning systems 25 (1), 154-171, 2013	124	2013
Introduction to the special section on educational data mining T Calders, M Pechenizkiy Acm Sigkdd Explorations Newsletter 13 (2), 3-6, 2012	94	2012
Dynamic integration with random forests A Tsymbal, M Pechenizkiy, P Cunningham European conference on machine learning, 801-808, 2006	93	2006
Process mining from educational data N Trcka, M Pechenizkiy, W van der Aalst Handbook of educational data mining, 123-142, 2010	85	2010
Class noise and supervised learning in medical domains: The effect of feature extraction M Pechenizkiy, A Tsymbal, S Puuronen, O Pechenizkiy 19th IEEE symposium on computer-based medical systems (CBMS'06), 708-713, 2006	81	2006
Process Mining Online Assessment Data. M Pechenizkiy, N Trcka, E Vasilyeva, W Van der Aalst, P De Bra International Working Group on Educational Data Mining, 2009	80	2009

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