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Foster Provost
Foster Provost
Bestätigte E-Mail-Adresse bei stern.nyu.edu
Titel
Zitiert von
Zitiert von
Jahr
Glossary of terms
R Kohavi, F Provost
Machine Learning 30, 271-274, 1998
16731998
Robust classification for imprecise environments
F Provost, T Fawcett
Machine learning 42 (3), 203-231, 2001
16202001
The Case Against Accuracy Estimation for Comparing Induction Algorithms
F Provost, T Fawcett, R Kohavi
Proceedings of ICML-98, 445-453, 1998
15681998
Data science and its relationship to big data and data-driven decision making
F Provost, T Fawcett
Big data 1 (1), 51-59, 2013
15322013
Adaptive fraud detection
T Fawcett, F Provost
Data mining and knowledge discovery 1 (3), 291-316, 1997
13011997
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
12882008
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
12332013
Quality management on amazon mechanical turk
PG Ipeirotis, F Provost, J Wang
Proceedings of the ACM SIGKDD workshop on human computation, 64-67, 2010
12232010
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
11422003
Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions
F Provost, T Fawcett
ACM SIGKDD, 43-48, 1997
1105*1997
Network-based marketing: Identifying likely adopters via consumer networks
S Hill, F Provost, C Volinsky
Statistical Science 21 (2), 256-276, 2006
7932006
Classification in networked data: A toolkit and a univariate case study.
SA Macskassy, F Provost
Journal of machine learning research 8 (5), 2007
6922007
Machine learning from imbalanced data sets 101
F Provost
Proceedings of the AAAI’2000 workshop on imbalanced data sets 68 (2000), 1-3, 2000
6622000
Tree induction for probability-based ranking
F Provost, P Domingos
Machine learning 52 (3), 199-215, 2003
6452003
The effect of class distribution on classifier learning: an empirical study
GM Weiss, F Provost
Rutgers University, 2001
5852001
Activity monitoring: Noticing interesting changes in behavior
T Fawcett, F Provost
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
5791999
Efficient progressive sampling
F Provost, D Jensen, T Oates
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
4851999
Tree induction vs. logistic regression: A learning-curve analysis
C Perlich, F Provost, J Simonoff
Journal of Machine Learning Research, 2003
4692003
Handling missing values when applying classification models
M Saar-Tsechansky, F Provost
Journal of Machine Learning Research, 2007
4342007
A survey of methods for scaling up inductive algorithms
F Provost, V Kolluri
Data mining and knowledge discovery 3 (2), 131-169, 1999
3941999
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