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

  • Authors:
  • Sreerama K. Murthy

  • Affiliations:
  • Siemens Corporate Research, Princeton, NJ 08540, USA. murthy@scr.siemens.com

  • Venue:
  • Data Mining and Knowledge Discovery
  • Year:
  • 1998

Quantified Score

Hi-index 0.01

Visualization

Abstract

Decision trees have proved to be valuable tools for thedescription, classification and generalization of data. Work onconstructing decision trees from data exists in multiple disciplinessuch as statistics, pattern recognition, decision theory, signalprocessing, machine learning and artificial neural networks.Researchers in these disciplines, sometimes working on quite differentproblems, identified similar issues and heuristics for decision treeconstruction. This paper surveys existing work on decision treeconstruction, attempting to identify the important issues involved,directions the work has taken and the current state of the art.