Applications of Machine Learning and Rule Induction,

Abstract

An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems. In this paper, we review the major paradigms for machine learning, including neural networks, instance-based methods, genetic learning, rule induction, and analytic approaches. We consider rule induction in greater detail and review some of its recent applications, in each case stating the problem, how rule induction was used, and the status of the resulting expert system. In closing, we identify the main stages in fielding an applied learning system and draw some lessons from successful applications.

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Document Details

Document Type
Technical Report
Publication Date
Feb 15, 1995
Accession Number
ADA292607

Entities

People

  • Herbert Simon
  • Pat Langley

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Computational Science
  • Computer Programming
  • Computer Science
  • Computers
  • Engineering
  • Expert Systems
  • Genetic Algorithms
  • Information Systems
  • Machine Learning
  • Neural Networks
  • Petroleum
  • Psychology
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Defense Acquisition Program Management

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Biotechnology