Data Mining and Knowledge Discovery

, Volume 2, Issue 4, pp 345–389

Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey

  • Sreerama K. Murthy
Article

DOI: 10.1023/A:1009744630224

Cite this article as:
Murthy, S.K. Data Mining and Knowledge Discovery (1998) 2: 345. doi:10.1023/A:1009744630224

Abstract

Decision trees have proved to be valuable tools for the description, classification and generalization of data. Work on constructing decision trees from data exists in multiple disciplines such as statistics, pattern recognition, decision theory, signal processing, machine learning and artificial neural networks. Researchers in these disciplines, sometimes working on quite different problems, identified similar issues and heuristics for decision tree construction. This paper surveys existing work on decision tree construction, attempting to identify the important issues involved, directions the work has taken and the current state of the art.

classificationtree-structured classifiersdata compaction

Copyright information

© Kluwer Academic Publishers 1998

Authors and Affiliations

  • Sreerama K. Murthy
    • 1
  1. 1.Siemens Corporate ResearchPrincetonUSA