Andrea Dal Pozzolo
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Calibrating probability with undersampling for unbalanced classification
A Dal Pozzolo, O Caelen, RA Johnson, G Bontempi
2015 IEEE symposium series on computational intelligence, 159-166, 2015
Learned lessons in credit card fraud detection from a practitioner perspective
A Dal Pozzolo, O Caelen, YA Le Borgne, S Waterschoot, G Bontempi
Expert systems with applications 41 (10), 4915-4928, 2014
Credit card fraud detection: a realistic modeling and a novel learning strategy
A Dal Pozzolo, G Boracchi, O Caelen, C Alippi, G Bontempi
IEEE transactions on neural networks and learning systems 29 (8), 3784-3797, 2017
Scarff: a scalable framework for streaming credit card fraud detection with spark
F Carcillo, A Dal Pozzolo, YA Le Borgne, O Caelen, Y Mazzer, ...
Information fusion 41, 182-194, 2018
When is undersampling effective in unbalanced classification tasks?
A Dal Pozzolo, O Caelen, G Bontempi
Machine Learning and Knowledge Discovery in Databases: European Conferenceá…, 2015
Credit card fraud detection and concept-drift adaptation with delayed supervised information
A Dal Pozzolo, G Boracchi, O Caelen, C Alippi, G Bontempi
2015 international joint conference on Neural networks (IJCNN), 1-8, 2015
Adaptive machine learning for credit card fraud detection
A Dal Pozzolo
UniversitÚ libre de Bruxelles, 2015
Racing for unbalanced methods selection
A Dal Pozzolo, O Caelen, S Waterschoot, G Bontempi
Intelligent Data Engineering and Automated Learning–IDEAL 2013: 14thá…, 2013
Using HDDT to avoid instances propagation in unbalanced and evolving data streams
A Dal Pozzolo, R Johnson, O Caelen, S Waterschoot, NV Chawla, ...
2014 International joint conference on neural networks (IJCNN), 588-594, 2014
Unbalanced: racing for unbalanced methods selection
AD Pozzolo, O Caelen, G Bontempi
R package version 2, 2015
Comparison of balancing techniques for unbalanced datasets
A Dal Pozzolo, O Caelen, G Bontempi
Mach. Learn. Gr. Univ. Libr. Bruxelles Belgium 16 (1), 732-735, 2010
Comparison of data mining techniques for insurance claim prediction
A Dal Pozzolo, G Moro, G Bontempi, DYA Le Borgne
Universita degli Studi di Bologna, 2011
Package ‘unbalanced’
A Dal Pozzolo, O Caelen, G Bontempi, MA Dal Pozzolo
Minimum redundancy maximum relevance: Mapreduce implementation using apache hadoop
C Reggiani, YA Le Borgne, A Dal Pozzolo, C Olsen, G Bontempi
Breadth Indicator, Contrarian Analysis to Financial Market Partecipation
A Dal Pozzolo
UniversitÓ degli Studi di Bologna, 2008
Gli indicatori di spessore, un'analisi contraria della partecipazione ai mercati finanziari
A Dal Pozzolo
Is Machine Learning useful for Fraud prevention?
A Dal Pozzolo
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