The Methodology of Applying Machine Learning: Problem Definition, Task Decomposition, and Technique Selection
Papers from the AAAI Workshop
Robert Engles, Program Chair
Technical Report WS-98-16 published by The AAAI Press, Menlo Park, California
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Contents
Preface / 1
Floor Verdenius, Robert Engels, David Aha
How to Get a Free Lunch: A Simple Cost Model for Machine Learning Applications / 1
P. Domingos
Quantitative Model Selection for Heterogeneous Time Series Learning / 8
W. Hsu and S. Ray
Research Issues Arising in Applying Machine Learning to Oil Slick Detection / 13
M. Kubat, R. Holte and S. Matwin
Introducing Inductive Methods in Knowledge Acquisition by Divide-and-Conquer / 20
M. W. van Someren and F. Verdenius
Specifying and Learning Inductive Learning Systems Using Ontologies / 29
A. Suyama and T. Yamaguchi
Applicability of Reinforcement Learning / 37
P. E. Utgoff and P. R. Cohen
Comparison of Techniques to Learn Agent Strategies in Adversal Games / 44
S. Whisenhunt and D. J. Cook
Using Machine Learning to Construct Legal Knowledge Based Systems / 49
J. Zeleznikow
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