Foster Provost
TitleCited byYear
Glossary of terms
R Kohavi, F Provost
Machine Learning 30, 271-274, 1998
2721*1998
Robust classification for imprecise environments
F Provost, T Fawcett
Machine learning 42 (3), 203-231, 2001
13722001
Adaptive fraud detection
T Fawcett, F Provost
Data mining and knowledge discovery 1 (3), 291-316, 1997
10931997
Get another label? improving data quality and data mining using multiple, noisy labelers
VS Sheng, F Provost, PG Ipeirotis
Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008
9882008
Quality management on amazon mechanical turk
PG Ipeirotis, F Provost, J Wang
Proceedings of the ACM SIGKDD workshop on human computation, 64-67, 2010
9792010
Analysis and visualization of classifier performance: Comparison under imprecise class and cost distributions.
FJ Provost, T Fawcett
KDD 97, 43-48, 1997
9651997
Learning when training data are costly: The effect of class distribution on tree induction
GM Weiss, F Provost
Journal of artificial intelligence research 19, 315-354, 2003
9252003
Data science and its relationship to big data and data-driven decision making
F Provost, T Fawcett
Big data 1 (1), 51-59, 2013
7642013
Data Science for Business: What you need to know about data mining and data-analytic thinking
F Provost, T Fawcett
" O'Reilly Media, Inc.", 2013
7002013
Network-based marketing: Identifying likely adopters via consumer networks
S Hill, F Provost, C Volinsky
Statistical Science 21 (2), 256-276, 2006
6352006
Classification in networked data: A toolkit and a univariate case study
SA Macskassy, F Provost
Journal of machine learning research 8 (May), 935-983, 2007
6242007
Tree induction for probability-based ranking
F Provost, P Domingos
Machine learning 52 (3), 199-215, 2003
5642003
Activity Monitoring: Noticing Interesting Changes in Behavior.
T Fawcett, FJ Provost
KDD 99, 53-62, 1999
5001999
Machine learning from imbalanced data sets 101
F Provost
Proceedings of the AAAI’2000 workshop on imbalanced data sets 68 (2000), 1-3, 2000
4502000
Efficient progressive sampling
F Provost, D Jensen, T Oates
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
4041999
Tree induction vs. logistic regression: A learning-curve analysis
C Perlich, F Provost, JS Simonoff
Journal of Machine Learning Research 4 (Jun), 211-255, 2003
3822003
The effect of class distribution on classifier learning: an empirical study
GM Weiss, F Provost
3522001
A survey of methods for scaling up inductive algorithms
F Provost, V Kolluri
Data mining and knowledge discovery 3 (2), 131-169, 1999
3421999
A simple relational classifier
SA Macskassy, F Provost
NEW YORK UNIV NY STERN SCHOOL OF BUSINESS, 2003
3292003
Handling missing values when applying classification models
M Saar-Tsechansky, F Provost
Journal of machine learning research 8 (Jul), 1623-1657, 2007
3282007
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Articles 1–20