Machine 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 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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