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Arno Knobbe
Arno Knobbe
LIACS, Leiden University
Bestätigte E-Mail-Adresse bei liacs.leidenuniv.nl - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
1802016
Diverse subgroup set discovery
M Van Leeuwen, A Knobbe
Data Mining and Knowledge Discovery 25, 208-242, 2012
1632012
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
1532021
Propositionalisation and aggregates
AJ Knobbe, M De Haas, A Siebes
European Conference on Principles of Data Mining and Knowledge Discovery …, 2001
1512001
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
1182017
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
1012015
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
942019
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
742011
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
652013
Flexible enrichment with cortana–software demo
M Meeng, A Knobbe
Proceedings of BeneLearn, 117-119, 2011
632011
Entropy-based discretization methods for ranking data
CR De Sá, C Soares, A Knobbe
Information Sciences 329, 921-936, 2016
622016
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