Pat Langley
Herbert A. Simon
Abstract
Machine learning is the study of computational methods for improving performance by mechanizing the acquisition of knowledge from experience. Expert performance requires much domain-specific knowledge, and knowledge engineering has produced hundreds of AI expert systems that are now used regularly in industry. Machine learning aims to provide increasing levels of automation in the knowledge engineering process, replacing much time-consuming human activity with automatic techniques that improve accuracy or efficiency by discovering and exploiting regularities in training data. The ultimate test of machine learning is its ability to produce systems that are used regularly in industry, education, and elsewhere.
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Index Terms
- Applications of machine learning and rule induction
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Reviews
Daniel L. Chester
Rule induction, one of the five basic paradigms in machine learning, is covered most interestingly in this paper. (The other four paradigms are neural networks, case-based learning, genetic algorithms, and analytic learning.) Most of the paper describes about 20 fielded applications of rule induction, wherein decision trees or condition-action rules are constructed from collected data. Some of the experiences reported suggest that rule induction can produce substantially better knowledge bases than those obtained by interviews of experts. Other reported experiences remind us of the importance of providing the rule induction process with an adequate set of features from which to formulate rules. This portion of the paper will be valuable to anyone interested in machine learning or expert systems. A discussion of how the rule induction paradigm is applied to problems closes the paper, although it says little about the paradigm itself. This discussion may be of particular interest to machine learning practitioners because the authors make some generalizations about the applications process that seldom appear in the literature. Several good references are provided for those who want to know more about the rule induction paradigm.
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