Peter Flach

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José Hernández-OralloVRAIN, Valencian Research Institute for Artificial Intelligence, Universitat Politecnica de ValenciaVerified email at upv.es
Meelis KullAssociate Professor, University of TartuVerified email at ut.ee
Tom DietheAmazon; University of BristolVerified email at bristol.ac.uk
César FerriVRAIN. Universitat Politècnica de ValènciaVerified email at dsic.upv.es
Nicolas LachicheAssociate professor in Computer Science, University of StrasbourgVerified email at unistra.fr
Niall TwomeyResearch Fellow, University of Bristol, United KingdomVerified email at bristol.ac.uk
Thomas GärtnerTU Wien (Technical University of Vienna)Verified email at tuwien.ac.at
Kacper SokolUniversity of BristolVerified email at bristol.ac.uk
Hao SongResearch Associate, University of BristolVerified email at bristol.ac.uk
Ian CraddockUniversity of BristolVerified email at bristol.ac.uk
Shaomin WuProfessor of Business/Applied Statistics, Kent Business School, University of KentVerified email at kent.ac.uk
Antonis KakasUniversity of CyprusVerified email at ucy.ac.cy
Johannes FürnkranzJohannes Kepler University, LinzVerified email at faw.jku.at
Simon RawlesUniversity of NottinghamVerified email at rawles.net
Louise Amanda Claire MillardUniversity of BristolVerified email at bristol.ac.uk
John LloydEmeritus Professor of Computer Science, The Australian National UniversityVerified email at cecs.anu.edu.au
Alex SmolaAmazon Web ServicesVerified email at smola.org
Blaz ZupanUniversity of LjubljanaVerified email at fri.uni-lj.si
Luc De Raedtprofessor, KU LeuvenVerified email at cs.kuleuven.be
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzVerified email at informatik.uni-mainz.de

Peter Flach

Professor of Artificial Intelligence, Department of Computer Science, University of Bristol

Verified email at bristol.ac.uk - Homepage

Artificial Intelligence Data Science Machine Learning Data Mining


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Machine learning: the art and science of algorithms that make sense of data P Flach Cambridge University Press, 2012	1083	2012
On graph kernels: Hardness results and efficient alternatives T Gärtner, P Flach, S Wrobel Learning theory and kernel machines, 129-143, 2003	998	2003
Multi-instance kernels T Gärtner, PA Flach, A Kowalczyk, AJ Smola ICML 2 (3), 7, 2002	609	2002
Rule evaluation measures: A unifying view N Lavrač, P Flach, B Zupan International Conference on Inductive Logic Programming, 174-185, 1999	554	1999
Subgroup discovery with CN2-SD N Lavrač, B Kavšek, P Flach, L Todorovski Journal of Machine Learning Research 5 (Feb), 153-188, 2004	471	2004
Learning decision trees using the area under the ROC curve C Ferri, P Flach, J Hernández-Orallo Icml 2, 139-146, 2002	379	2002
Propositionalization approaches to relational data mining S Kramer, N Lavrač, P Flach Relational data mining, 262-291, 2001	375	2001
The geometry of ROC space: understanding machine learning metrics through ROC isometrics PA Flach Proceedings of the 20th international conference on machine learning (ICML …, 2003	334	2003
Roc ‘n’rule learning—towards a better understanding of covering algorithms J Fürnkranz, PA Flach Machine learning 58 (1), 39-77, 2005	291	2005
Abduction and Induction: Essays on their relation and integration PA Flach, AC Kakas Kluwer Academic Publishers, 2000	268*	2000
Kernels and distances for structured data T Gärtner, JW Lloyd, PA Flach Machine Learning 57 (3), 205-232, 2004	206	2004
Bridging e-health and the internet of things: The sphere project N Zhu, T Diethe, M Camplani, L Tao, A Burrows, N Twomey, D Kaleshi, ... IEEE Intelligent Systems 30 (4), 39-46, 2015	202	2015
Confirmation-guided discovery of first-order rules with Tertius PA Flach, N Lachiche Machine learning 42 (1), 61-95, 2001	194	2001
A coherent interpretation of AUC as a measure of aggregated classification performance PA Flach, J Hernández-Orallo, C Ferri Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011	189	2011
Database dependency discovery: a machine learning approach PA Flach, I Savnik AI communications 12 (3), 139-160, 1999	187	1999
A unified view of performance metrics: Translating threshold choice into expected classification loss J Hernández-Orallo, P Flach, C Ferri Ramírez Journal of Machine Learning Research 13, 2813-2869, 2012	185	2012
Simply logical intelligent reasoning by example PA Flach	176	1994
Naive Bayesian classification of structured data PA Flach, N Lachiche Machine Learning 57 (3), 233-269, 2004	172	2004
Comparative evaluation of approaches to propositionalization MA Krogel, S Rawles, F Železný, PA Flach, N Lavrač, S Wrobel International Conference on Inductive Logic Programming, 197-214, 2003	169	2003
Improving accuracy and cost of two-class and multi-class probabilistic classifiers using ROC curves N Lachiche, PA Flach Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003	168	2003

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