Peter Flach 个人学术档案 - 学术资源搜索

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Meelis KullAssociate Professor, University of Tartu在 ut.ee 的电子邮件经过验证
José Hernández-OralloVRAIN (UPV), ValGRAI, CFI, CSER.在 upv.es 的电子邮件经过验证
Tom DietheAstraZeneca; University of Bristol在 bristol.ac.uk 的电子邮件经过验证
Cèsar FerriVRAIN. Universitat Politècnica de València在 dsic.upv.es 的电子邮件经过验证
Kacper SokolETH Zürich在 inf.ethz.ch 的电子邮件经过验证
Nicolas LachicheProfessor in Computer Science, University of Strasbourg在 unistra.fr 的电子邮件经过验证
Niall TwomeyAmazon; University of Bristol (honorary)在 bristol.ac.uk 的电子邮件经过验证
Raúl Santos-RodríguezUniversity of Bristol在 bristol.ac.uk 的电子邮件经过验证
Thomas GärtnerTU Wien (Technical University of Vienna)在 tuwien.ac.at 的电子邮件经过验证
Hao SongAmazon; University of Bristol在 amazon.com 的电子邮件经过验证
Miquel Perelló-NietoResearch Associate at University of Bristol在 bristol.ac.uk 的电子邮件经过验证
Ian CraddockUniversity of Bristol在 bristol.ac.uk 的电子邮件经过验证
Antonis KakasUniversity of Cyprus在 ucy.ac.cy 的电子邮件经过验证
Simon PriceResearch Fellow, University of Bristol在 bristol.ac.uk 的电子邮件经过验证
Tijl De BieFull Professor, Ghent University在 ugent.be 的电子邮件经过验证
Shaomin WuProfessor of Business/Applied Statistics, Kent Business School, University of Kent在 kent.ac.uk 的电子邮件经过验证
Stefan WrobelFraunhofer IAIS and University of Bonn在 iais.fraunhofer.de 的电子邮件经过验证
Louise AC MillardUniversity of Bristol在 bristol.ac.uk 的电子邮件经过验证
Johannes FürnkranzJohannes Kepler University, Linz在 faw.jku.at 的电子邮件经过验证
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro University在 cs.kuleuven.be 的电子邮件经过验证

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Peter Flach

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

在 bristol.ac.uk 的电子邮件经过验证 - 首页

Artificial Intelligence Data Science Machine Learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Machine learning: the art and science of algorithms that make sense of data P Flach Cambridge university press, 2012	1885	2012
On graph kernels: Hardness results and efficient alternatives T Gärtner, P Flach, S Wrobel Learning Theory and Kernel Machines: 16th Annual Conference on Learning …, 2003	1269	2003
Multi-instance kernels T Gärtner, PA Flach, A Kowalczyk, AJ Smola ICML 2 (3), 7, 2002	719	2002
Rule evaluation measures: A unifying view N Lavrač, P Flach, B Zupan International Conference on Inductive Logic Programming, 174-185, 1999	597	1999
Subgroup discovery with CN2-SD N Lavrač, B Kavšek, P Flach, L Todorovski Journal of Machine Learning Research 5 (Feb), 153-188, 2004	570	2004
CRISP-DM twenty years later: From data mining processes to data science trajectories F Martínez-Plumed, L Contreras-Ochando, C Ferri, J Hernández-Orallo, ... IEEE transactions on knowledge and data engineering 33 (8), 3048-3061, 2019	465	2019
Learning decision trees using the area under the ROC curve C Ferri, P Flach, J Hernández-Orallo Icml 2, 139-146, 2002	438	2002
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	427	2003
Precision-recall-gain curves: PR analysis done right P Flach, M Kull Advances in neural information processing systems 28, 2015	425	2015
Propositionalization approaches to relational data mining S Kramer, N Lavrač, P Flach Relational data mining, 262-291, 2001	413	2001
FACE: feasible and actionable counterfactual explanations R Poyiadzi, K Sokol, R Santos-Rodriguez, T De Bie, P Flach Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 344-350, 2020	365	2020
Explainability fact sheets: A framework for systematic assessment of explainable approaches K Sokol, P Flach Proceedings of the 2020 conference on fairness, accountability, and …, 2020	334	2020
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	332	2011
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with dirichlet calibration M Kull, M Perello Nieto, M Kängsepp, T Silva Filho, H Song, P Flach Advances in neural information processing systems 32, 2019	321	2019
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	321	2015
Roc ‘n’rule learning—towards a better understanding of covering algorithms J Fürnkranz, PA Flach Machine learning 58, 39-77, 2005	315	2005
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining JJF Elder IV, F Fogelman-Soulié, P Flach, M Zaki Association for Computing Machinery (ACM), 2009	287	2009
Abduction and Induction: Essays on their relation and integration PA Flach, AC Kakas Kluwer Academic Publishers, 2000	285	2000
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	259	2012
Database dependency discovery: a machine learning approach PA Flach, I Savnik AI communications 12 (3), 139-160, 1999	237	1999

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