Applications of machine learning and rule induction

Authors:
Pat Langley;Herbert A. Simon
Affiliations:
Stanford Univ., Stanford, CA;Carnegie Mellon Univ., Pittsburgh, PA
Venue:
Communications of the ACM
Year:
1995

Citing 9
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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.