Peter Flach
Peter Flach
Professor of Artificial Intelligence, Department of Computer Science, University of Bristol
Verified email at bristol.ac.uk - Homepage
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
9722012
On graph kernels: Hardness results and efficient alternatives
T Gärtner, P Flach, S Wrobel
Learning theory and kernel machines, 129-143, 2003
9392003
Multi-instance kernels
T Gärtner, PA Flach, A Kowalczyk, AJ Smola
ICML 2 (3), 7, 2002
5932002
Rule evaluation measures: A unifying view
N Lavrač, P Flach, B Zupan
International Conference on Inductive Logic Programming, 174-185, 1999
5411999
Subgroup discovery with CN2-SD
N Lavrač, B Kavšek, P Flach, L Todorovski
Journal of Machine Learning Research 5 (Feb), 153-188, 2004
4662004
Learning decision trees using the area under the ROC curve
C Ferri, P Flach, J Hernández-Orallo
Icml 2, 139-146, 2002
3722002
Propositionalization approaches to relational data mining
S Kramer, N Lavrač, P Flach
Relational data mining, 262-291, 2001
3682001
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
3252003
Roc ‘n’rule learning—towards a better understanding of covering algorithms
J Fürnkranz, PA Flach
Machine Learning 58 (1), 39-77, 2005
2822005
Abduction and Induction: Essays on their relation and integration
PA Flach, AC Kakas
Kluwer Academic Publishers, 2000
266*2000
Kernels and distances for structured data
T Gärtner, JW Lloyd, PA Flach
Machine Learning 57 (3), 205-232, 2004
2002004
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
1822015
Confirmation-guided discovery of first-order rules with Tertius
PA Flach, N Lachiche
Machine learning 42 (1-2), 61-95, 2001
1812001
Database dependency discovery: a machine learning approach
PA Flach, I Savnik
AI communications 12 (3), 139-160, 1999
1801999
A unified view of performance metrics: translating threshold choice into expected classification loss
J Hernández-Orallo, P Flach, C Ferri
The Journal of Machine Learning Research 13 (1), 2813-2869, 2012
1792012
Simply logical intelligent reasoning by example
PA Flach
1731994
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
1722011
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
1672003
Naive Bayesian classification of structured data
PA Flach, N Lachiche
Machine Learning 57 (3), 233-269, 2004
1662004
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
1642003
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