Abstract
M achine 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.
Keywords
Computer scienceAutomationExpert systemKnowledge acquisitionMachine learningDomain knowledgeProcess (computing)Artificial intelligenceDomain (mathematical analysis)Knowledge engineeringTest (biology)Rule inductionSoftware engineeringEngineering
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Publication Info
- Year
- 1995
- Type
- article
- Volume
- 38
- Issue
- 11
- Pages
- 54-64
- Citations
- 497
- Access
- Closed
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Cite This
Pat Langley,
Herbert A. Simon
(1995).
Applications of machine learning and rule induction.
Communications of the ACM
, 38
(11)
, 54-64.
https://doi.org/10.1145/219717.219768
Identifiers
- DOI
- 10.1145/219717.219768