Stebėti
Foster Provost
Foster Provost
Patvirtintas el. paštas stern.nyu.edu
Pavadinimas
Cituota
Cituota
Metai
Data science and its relationship to big data and data-driven decision making
F Provost, T Fawcett
Big data 1 (1), 51-59, 2013
21752013
Glossary of terms
R Kohavi, F Provost
Machine Learning 30, 271-274, 1998
18901998
Robust classification for imprecise environments
F Provost, T Fawcett
Machine learning 42, 203-231, 2001
17352001
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
17252013
The Case Against Accuracy Estimation for Comparing Induction Algorithms
F Provost, T Fawcett, R Kohavi
Proceedings of ICML-98, 445-453, 1998
16681998
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
14482008
Adaptive fraud detection
T Fawcett, F Provost
Data mining and knowledge discovery 1 (3), 291-316, 1997
13731997
Quality management on amazon mechanical turk
PG Ipeirotis, F Provost, J Wang
Proceedings of the ACM SIGKDD workshop on human computation, 64-67, 2010
13292010
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
12432003
Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions
F Provost, T Fawcett
Proceedings of the Third International Conference on Knowledge Discovery and …, 1997
1169*1997
Network-based marketing: Identifying likely adopters via consumer networks
S Hill, F Provost, C Volinsky
8792006
Machine learning from imbalanced data sets 101
F Provost
Proceedings of the AAAI’2000 workshop on imbalanced data sets 68 (2000), 1-3, 2000
8062000
Classification in networked data: A toolkit and a univariate case study.
SA Macskassy, F Provost
Journal of machine learning research 8 (5), 2007
7152007
Tree induction for probability-based ranking
F Provost, P Domingos
Machine learning 52, 199-215, 2003
6992003
Activity monitoring: Noticing interesting changes in behavior
T Fawcett, F Provost
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
5971999
Efficient progressive sampling
F Provost, D Jensen, T Oates
Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999
5341999
Tree induction vs. logistic regression: A learning-curve analysis
C Perlich, F Provost, J Simonoff
Journal of Machine Learning Research, 2003
5222003
The effect of class distribution on classifier learning: an empirical study
GM Weiss, F Provost
Rutgers University, 2001
5082001
Handling missing values when applying classification models
M Saar-Tsechansky, F Provost
Journal of Machine Learning Research, 2007
5012007
Privacy-sensitive methods, systems, and media for targeting online advertisements using brand affinity modeling
R Hook, FJ Provost, B May, B Dalessandro
US Patent App. 12/700,728, 2010
4252010
Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.
Straipsniai 1–20