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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 - L. 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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