---
title: "Lookahead and Pathology in Decision Tree Induction"
authors:
  - "Sreerama K. Murthy"
  - "Steven Salzberg"
doi: ""
url: "https://ijcai.org/proceedings/1995/133"
pdf: "https://ijcai.org/proceedings/1995/0133.pdf"
venue: "Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence"
year: 1995
pages: "1025-1032"
track: "Learning"
keywords:
---

# Lookahead and Pathology in Decision Tree Induction

Sreerama K. Murthy, Steven Salzberg

*Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence*, pages 1025-1032.

## Abstract

The standard approach to decision tree induction is a top-down , greedy algorithm that makes locally optimal, irrevocable decisions at each node of a tree. In this paper, we empirically study an alternative approach, in which the algorithms use one-level lookahead to decide what test to use at a node . We systematically compare, using a very large number of real and artificial data sets, th e quality of decision trees induced by the greedy approach to that of trees induced using look ahead. The main observations from our experiments are: (i) the greedy approach consistently produced trees that were just as accurate as trees produced with the much more expensive lookahead step; and (ii) we observed many instances of pathology, i.e. , lookahead produced trees that were both l arger and less accurate than trees produced without it.