Machine Learning, Volume 13

Volume 13, 1993

• Ming Tan:
  Cost-Sensitive Learning of Classification Knowledge and Its Applications in Robotics. 7-33
  
• Yousri El Fattah, Paul O'Rorke:
  Explanation-Based Learning for Diagnosis. 35-70
  
• Geoffrey G. Towell, Jude W. Shavlik:
  Extracting Refined Rules from Knowledge-Based Neural Networks. 71-101
  
• Andrew W. Moore, Christopher G. Atkeson:
  Prioritized Sweeping: Reinforcement Learning With Less Data and Less Time. 103-130
  
• Ron Kohavi, Scott Benson:
  Research Note on Decision Lists. 131-134
  
• Cullen Schaffer:
  Selecting a Classification Method by Cross-Validation. 135-143
  
• Lisa Hellerstein:
  Book Review: "Machine Learning: A Theoretical Approach". 145-149
  
• B. K. Natarajan:
  A Reply to Hellerstein's Book Review of Machine Learning: A Theoretical Approach. 151-152
  
• Kenneth A. De Jong, William M. Spears, Diana F. Gordon:
  Using Genetic Algorithms for Concept Learning. 161-188
  
• Cezary Z. Janikow:
  A Knowledge-Intensive Genetic Algorithm for Supervised Learning. 189-228
  
• David Perry Greene, Stephen F. Smith:
  Competition-Based Induction of Decision Models from Examples. 229-257
  
• Darrell Whitley:
  Genetic Reinforcement Learning for Neurocontrol Problems. 259-284
  
• Stephanie Forrest, Melanie Mitchell:
  What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation. 285-319
  

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