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Arno Knobbe
Arno Knobbe
LIACS, Leiden University
Verified email at liacs.leidenuniv.nl - Homepage
Title
Cited by
Cited by
Year
Exceptional model mining
D Leman, A Feelders, A Knobbe
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008
1932008
Exceptional Model Mining: Supervised descriptive local pattern mining with complex target concepts
W Duivesteijn, AJ Feelders, A Knobbe
Data Mining and Knowledge Discovery 30, 47-98, 2016
1792016
Diverse subgroup set discovery
M Van Leeuwen, A Knobbe
Data Mining and Knowledge Discovery 25, 208-242, 2012
1622012
Propositionalisation and aggregates
AJ Knobbe, M De Haas, A Siebes
European Conference on Principles of Data Mining and Knowledge Discovery …, 2001
1502001
Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review
FR Goes, LA Meerhoff, MJO Bueno, DM Rodrigues, FA Moura, MS Brink, ...
European Journal of Sport Science 21 (4), 481-496, 2021
1442021
Pattern teams
AJ Knobbe, EKY Ho
European Conference on Principles of Data Mining and Knowledge Discovery …, 2006
1302006
From local patterns to global models: the LeGo approach to data mining
A Knobbe, B Crémilleux, J Fürnkranz, M Scholz
LeGo 8, 1-16, 2008
1262008
Social competence at the playground: Preschoolers during recess
G Veiga, W De Leng, R Cachucho, L Ketelaar, JN Kok, A Knobbe, C Neto, ...
Infant and Child Development 26 (1), e1957, 2017
1152017
System and method for generating performance models of complex information technology systems
PW Adriaans, AJ Knobbe, M Gathier
US Patent 6,311,175, 2001
1062001
Football Player's Performance and Market Value.
M He, R Cachucho, AJ Knobbe
Mlsa@ pkdd/ecml, 87-95, 2015
992015
Multi-relational data mining
BLJ Kaczmarek, AJ Knobbe
Ios Press, 2006
962006
Multi-relational data mining
A Knobbe, H Blockeel, A Siebes, D van der Wallen
Proceedings of the 9th Belgian-Dutch Conference on Machine Learning, 61-74, 1999
951999
A defect classification methodology for sewer image sets with convolutional neural networks
D Meijer, L Scholten, F Clemens, A Knobbe
Automation in Construction 104, 281-298, 2019
902019
Maximally informative k-itemsets and their efficient discovery
AJ Knobbe, EKY Ho
Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006
822006
Subgroup discovery meets bayesian networks--an exceptional model mining approach
W Duivesteijn, A Knobbe, A Feelders, M van Leeuwen
2010 IEEE International Conference on Data Mining, 158-167, 2010
812010
Exploiting false discoveries--statistical validation of patterns and quality measures in subgroup discovery
W Duivesteijn, A Knobbe
2011 IEEE 11th International Conference on Data Mining, 151-160, 2011
732011
Multi-relational decision tree induction
AJ Knobbe, A Siebes, D van der Wallen
Principles of Data Mining and Knowledge Discovery: Third European Conference …, 1999
731999
Benefits of a short, practical questionnaire to measure subjective perception of nasal appearance after aesthetic rhinoplasty
PJFM Lohuis, S Hakim, W Duivesteijn, A Knobbe, AJ Tasman
Plastic and reconstructive surgery 132 (6), 913e-923e, 2013
642013
Flexible enrichment with cortana–software demo
M Meeng, A Knobbe
Proceedings of BeneLearn, 117-119, 2011
632011
Subgroup discovery in smart electricity meter data
N Jin, P Flach, T Wilcox, R Sellman, J Thumim, A Knobbe
IEEE Transactions on Industrial Informatics 10 (2), 1327-1336, 2014
612014
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