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ORCIDMachine Learning, Volume 57, 2004
Volume 57, Number 1-2, October 2004
- Nada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach
:
Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned. 115-143 - Nada Lavrac, Hiroshi Motoda, Tom Fawcett:
Editorial: Data Mining Lessons Learned. 5-11 - Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans:
Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. 13-34 - Chun-Nan Hsu, Hao-Hsiang Chung, Han-Shen Huang:
Mining Skewed and Sparse Transaction Data for Personalized Shopping Recommendation. 35-59 - Mark-A. Krogel, Tobias Scheffer:
Multi-Relational Learning, Text Mining, and Semi-Supervised Learning for Functional Genomics. 61-81 - Ron Kohavi, Llew Mason, Rajesh Parekh, Zijian Zheng:
Lessons and Challenges from Mining Retail E-Commerce Data. 83-113 - Tom M. Mitchell, Rebecca A. Hutchinson, Radu Stefan Niculescu, Francisco Pereira, Xuerui Wang, Marcel Adam Just, Sharlene D. Newman:
Learning to Decode Cognitive States from Brain Images. 145-175 - Peter van der Putten, Maarten van Someren:
A Bias-Variance Analysis of a Real World Learning Problem: The CoIL Challenge 2000. 177-195
Volume 57, Number 3, December 2004
- Stan Matwin:
Guest Editorial. 203-204 - Thomas Gärtner, John W. Lloyd, Peter A. Flach:
Kernels and Distances for Structured Data. 205-232 - Peter A. Flach, Nicolas Lachiche:
Naive Bayesian Classification of Structured Data. 233-269 - Kurt Driessens, Saso Dzeroski:
Integrating Guidance into Relational Reinforcement Learning. 271-304 - Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel:
Compact Representation of Knowledge Bases in Inductive Logic Programming. 305-333
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