Ron Kohavi

Alex Deng, Ya Xu, Ron Kohavi, Toby Walker: Improving the sensitivity of online controlled experiments by utilizing pre-experiment data. WSDM 2013: 123-132

Ron Kohavi, Alex Deng, Brian Frasca, Roger Longbotham, Toby Walker, Ya Xu: Trustworthy online controlled experiments: five puzzling outcomes explained. KDD 2012: 786-794

Ron Kohavi: Online controlled experiments: introduction, learnings, and humbling statistics. RecSys 2012: 1-2

Ron Kohavi, Roger Longbotham, Toby Walker: Online Experiments: Practical Lessons. IEEE Computer 43(9): 82-85 (2010)

Ron Kohavi, Roger Longbotham: Unexpected results in online controlled experiments. SIGKDD Explorations 12(2): 31-35 (2010)

Ron Kohavi, Roger Longbotham, Dan Sommerfield, Randal M. Henne: Controlled experiments on the web: survey and practical guide. Data Min. Knowl. Discov. 18(1): 140-181 (2009)

Thomas Crook, Brian Frasca, Ron Kohavi, Roger Longbotham: Seven pitfalls to avoid when running controlled experiments on the web. KDD 2009: 1105-1114

Ron Kohavi, Roger Longbotham: Online Experiments: Lessons Learned. IEEE Computer 40(9): 103-105 (2007)

Ron Kohavi, Randal M. Henne, Dan Sommerfield: Practical guide to controlled experiments on the web: listen to your customers not to the hippo. KDD 2007: 959-967

Ron Kohavi: Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce. PKDD 2005: 7

Ron Kohavi, Llew Mason, Rajesh Parekh, Zijian Zheng: Lessons and Challenges from Mining Retail E-Commerce Data. Machine Learning 57(1-2): 83-113 (2004)

Ron Kohavi, Rajesh Parekh: Visualizing RFM Segmentation. SDM 2004

Won Kim, Ron Kohavi, Johannes Gehrke, William DuMouchel (Eds.): Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, USA, August 22-25, 2004. ACM 2004, isbn 1-58113-888-1

Ron Kohavi, Neal Rothleder, Evangelos Simoudis: Emerging trends in business analytics. Commun. ACM 45(8): 45-48 (2002)

Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava: Web Mining. Data Min. Knowl. Discov. 6(1): 5-8 (2002)

Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava (Eds.): WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points, Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers. Lecture Notes in Computer Science 2356, Springer 2002, isbn 3-540-43969-2

Ron Kohavi, Foster J. Provost: Applications of Data Mining to Electronic Commerce. Data Min. Knowl. Discov. 5(1/2): 5-10 (2001)

Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng: Integrating E-Commerce and Data Mining: Architecture and Challenges. ICDM 2001: 27-34

Ron Kohavi: Mining e-commerce data: the good, the bad, and the ugly. KDD 2001: 8-13

Zijian Zheng, Ron Kohavi, Llew Mason: Real world performance of association rule algorithms. KDD 2001: 401-406

Ron Kohavi: Mining E-Commerce Data: The Good, the Bad, and the Ugly. PAKDD 2001: 2

Ron Kohavi, Mehran Sahami: Integrating Data Mining into Vertical Solutions. SIGKDD Explorations 1(2): 55-58 (2000)

Ron Kohavi, Carla E. Brodley, Brian Frasca, Llew Mason, Zijian Zheng: KDD-Cup 2000 Organizers' Report: Peeling the Onion. SIGKDD Explorations 2(2): 86-98 (2000)

Myra Spiliopoulou, Jaideep Srivastava, Ron Kohavi, Brij M. Masand: WEBKDD 2000 - Web Mining for E-Commerce. SIGKDD Explorations 2(2): 106-107 (2000)

Ron Kohavi, Myra Spiliopoulou, Jaideep Srivastava: Web mining for e-commerce (workshop session - title only). KDD 2000: 534

Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng: Integrating E-Commerce and Data Mining: Architecture and Challenges. CoRR cs.LG/0007026 (2000)

Ron Kohavi, Foster J. Provost: Applications of Data Mining to Electronic Commerce. CoRR cs.LG/0010006 (2000)

Eric Bauer, Ron Kohavi: An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. Machine Learning 36(1-2): 105-139 (1999)

Foster J. Provost, Ron Kohavi: Guest Editors' Introduction: On Applied Research in Machine Learning. Machine Learning 30(2-3): 127-132 (1998)

Jeffrey P. Bradford, Clayton Kunz, Ron Kohavi, Clifford Brunk, Carla E. Brodley: Pruning Decision Trees with Misclassification Costs. ECML 1998: 131-136

Foster J. Provost, Tom Fawcett, Ron Kohavi: The Case against Accuracy Estimation for Comparing Induction Algorithms. ICML 1998: 445-453

Ron Kohavi, Dan Sommerfield: Targeting Business Users with Decision Table Classifiers. KDD 1998: 249-253

Ron Kohavi, George H. John: Wrappers for Feature Subset Selection. Artif. Intell. 97(1-2): 273-324 (1997)

Ron Kohavi, Dan Sommerfield, James Dougherty: Data Mining Using MLC a Machine Learning Library in C++. International Journal on Artificial Intelligence Tools 6(4): 537-566 (1997)

Ron Kohavi, Clayton Kunz: Option Decision Trees with Majority Votes. ICML 1997: 161-169

Clifford Brunk, James Kelly, Ron Kohavi: MineSet: An Integrated System for Data Mining. KDD 1997: 135-138

Jerome H. Friedman, Ron Kohavi, Yeogirl Yun: Lazy Decision Trees. AAAI/IAAI, Vol. 1 1996: 717-724

Ron Kohavi, David Wolpert: Bias Plus Variance Decomposition for Zero-One Loss Functions. ICML 1996: 275-283

Ron Kohavi, Dan Sommerfield, James Dougherty: Data Mining Using MLC++: A Machine Learning Library in C++. ICTAI 1996: 234-245

Ron Kohavi, Mehran Sahami: Error-Based and Entropy-Based Discretization of Continuous Features. KDD 1996: 114-119

Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. KDD 1996: 202-207

Ron Kohavi: The Power of Decision Tables. ECML 1995: 174-189

James Dougherty, Ron Kohavi, Mehran Sahami: Supervised and Unsupervised Discretization of Continuous Features. ICML 1995: 194-202

Ron Kohavi, George H. John: Autmatic Parameter Selection by Minimizing Estimated Error. ICML 1995: 304-312

Ron Kohavi, Chia-Hsin Li: Oblivious Decision Trees, Graphs, and Top-Down Pruning. IJCAI 1995: 1071-1079

Ron Kohavi: A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. IJCAI 1995: 1137-1145

Ron Kohavi, Dan Sommerfield: Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology. KDD 1995: 192-197

Ron Kohavi: Bottom-Up Induction of Oblivious Read-Once Decision Graphs: Strengths and Limitations. AAAI 1994: 613-618

Ron Kohavi: Bottom-Up Induction of Oblivious Read-Once Decision Graphs. ECML 1994: 154-169

George H. John, Ron Kohavi, Karl Pfleger: Irrelevant Features and the Subset Selection Problem. ICML 1994: 121-129

Ron Kohavi, George H. John, Richard Long, David Manley, Karl Pfleger: MLC++: A Machine Learning Library in C++. ICTAI 1994: 740-743

Ron Kohavi, Scott Benson: Research Note on Decision Lists. Machine Learning 13: 131-134 (1993)