Data science and its relationship to big data and data-driven decision making F Provost, T Fawcett Big data 1 (1), 51-59, 2013 | 2263 | 2013 |
Glossary of terms R Kohavi, F Provost Machine Learning 30, 271-274, 1998 | 1912 | 1998 |
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 | 1778 | 2013 |
Robust classification for imprecise environments F Provost, T Fawcett Machine learning 42, 203-231, 2001 | 1763 | 2001 |
The Case Against Accuracy Estimation for Comparing Induction Algorithms F Provost, T Fawcett, R Kohavi Proceedings of ICML-98, 445-453, 1998 | 1672 | 1998 |
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 | 1476 | 2008 |
Adaptive fraud detection T Fawcett, F Provost Data mining and knowledge discovery 1 (3), 291-316, 1997 | 1389 | 1997 |
Quality management on amazon mechanical turk PG Ipeirotis, F Provost, J Wang Proceedings of the ACM SIGKDD workshop on human computation, 64-67, 2010 | 1340 | 2010 |
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 | 1255 | 2003 |
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 | 1175* | 1997 |
Network-based marketing: Identifying likely adopters via consumer networks S Hill, F Provost, C Volinsky | 885 | 2006 |
Machine learning from imbalanced data sets 101 F Provost Proceedings of the AAAI’2000 workshop on imbalanced data sets 68 (2000), 1-3, 2000 | 811 | 2000 |
Classification in networked data: A toolkit and a univariate case study. SA Macskassy, F Provost Journal of machine learning research 8 (5), 2007 | 712 | 2007 |
Tree induction for probability-based ranking F Provost, P Domingos Machine learning 52, 199-215, 2003 | 698 | 2003 |
The effect of class distribution on classifier learning: an empirical study GM Weiss, F Provost | 638 | 2001 |
Activity monitoring: Noticing interesting changes in behavior T Fawcett, F Provost Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 602 | 1999 |
Efficient progressive sampling F Provost, D Jensen, T Oates Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 539 | 1999 |
Tree induction vs. logistic regression: A learning-curve analysis C Perlich, F Provost, J Simonoff Journal of Machine Learning Research, 2003 | 520 | 2003 |
Handling missing values when applying classification models M Saar-Tsechansky, F Provost Journal of Machine Learning Research, 2007 | 509 | 2007 |
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 | 435 | 2010 |