| A study of cross-validation and bootstrap for accuracy estimation and model selection R Kohavi Ijcai 14 (2), 1137-1145, 1995 | 17317 | 1995 |
| Wrappers for feature subset selection R Kohavi, GH John Artificial intelligence 97 (1-2), 273-324, 1997 | 11935 | 1997 |
| An empirical comparison of voting classification algorithms: Bagging, boosting, and variants E Bauer, R Kohavi Machine learning 36, 105-139, 1999 | 3763 | 1999 |
| Irrelevant features and the subset selection problem GH John, R Kohavi, K Pfleger Machine learning proceedings 1994, 121-129, 1994 | 3732 | 1994 |
| Supervised and unsupervised discretization of continuous features J Dougherty, R Kohavi, M Sahami Machine learning proceedings 1995, 194-202, 1995 | 3105 | 1995 |
| Scaling up the accuracy of naive-bayes classifiers: A decision-tree hybrid. R Kohavi Kdd 96, 202-207, 1996 | 2432 | 1996 |
| The case against accuracy estimation for comparing induction algorithms. FJ Provost, T Fawcett, R Kohavi ICML 98, 445-453, 1998 | 1974* | 1998 |
| Glossary of terms R Kohavi Machine learning 30, 271-274, 1998 | 1912 | 1998 |
| The power of decision tables R Kohavi European conference on machine learning, 174-189, 1995 | 1155 | 1995 |
| Bias plus variance decomposition for zero-one loss functions R Kohavi, DH Wolpert ICML 96, 275-283, 1996 | 1035 | 1996 |
| Controlled experiments on the web: survey and practical guide R Kohavi, R Longbotham, D Sommerfield, RM Henne Data mining and knowledge discovery 18, 140-181, 2009 | 960 | 2009 |
| Real world performance of association rule algorithms Z Zheng, R Kohavi, L Mason Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001 | 740 | 2001 |
| Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology. R Kohavi, D Sommerfield KDD 95, 192-197, 1995 | 531 | 1995 |
| Wrappers for performance enhancement and oblivious decision graphs R Kohavi stanford university, 1996 | 498 | 1996 |
| Emerging trends in business analytics R Kohavi, NJ Rothleder, E Simoudis Communications of the ACM 45 (8), 45-48, 2002 | 488 | 2002 |
| Data mining using MLC++: A machine learning library in C++ R Kohavi, D Sommerfield, J Dougherty Int. J. on Artificial Intelligence Tools 6 (4), 537-566, 1997 | 488 | 1997 |
| Data mining using MLC++, a machine learning library in C++ R Kohavi, D Sommerfield, J Dougherty Tools with Artificial Intelligence, 1996., Proceedings Eighth IEEE …, 1996 | 488* | 1996 |
| Data mining using MLC++, a machine learning library in C++ R Kohavi, D Sommerfield, J Dougherty Tools with Artificial Intelligence, 1996., Proceedings Eighth IEEE …, 1996 | 488* | 1996 |
| Data mining using MLC++: A machine learning library in C++ R Kohavi, D Sommerfield, J Dougherty Tools with Artificial Intelligence 6 (4), 234-245, 1996 | 488* | 1996 |
| Online controlled experiments and A/B tests R Kohavi, R Longbotham Encyclopedia of machine learning and data mining, 1-11, 2015 | 485 | 2015 |
George JohnStanford University在 cs.stanford.edu 的电子邮件经过验证
