Guiding Genetic Program Based Data Mining Using Fuzzy Rules

Abstract

A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program is discussed. A genetic program (GP) is an algorithm that evolves other algorithms or mathematical expressions. Methods for accelerating convergence of the data mining procedure are examined. The methods include introducing fuzzy rules into the GP and a new innovation based on computer algebra. Experimental results related to using computer algebra are given. Comparisons between trees created using a genetic program and those constructed solely by interviewing experts are made. Connections to past GP based data mining procedures for evolving fuzzy decision trees are established. Finally, experimental methods that have been used to validate the data mining algorithm are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA524875

Entities

People

  • James F. Smith Iii
  • Thanhvu H. Nguyen

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Computer Programs
  • Computers
  • Control Systems
  • Convergence
  • Data Mining
  • Databases
  • Fuzzy Logic
  • Genetic Algorithms
  • Logic
  • Military Research
  • Refractive Index
  • Reliability
  • Unmanned Aerial Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology
  • Space