Title

Experiments With An Innovative Tree Pruning Algorithm

Keywords

2-norm; C4.5; CART; Classification; Decision tree; Pruning

Abstract

The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorithms tend to have some or all of the following difficulties: 1) lack of theoretical support; 2) high computational complexity; 3) dependence on validation; 4) complicated implementation. The 2-norm pruning algorithm proposed here addresses all of the above difficulties. This paper demonstrates the experimental results of the comparison among the 2-norm pruning algorithm and two classical pruning algorithms, the Minimal Cost-Complexity algorithm (used in CART) and the Error-based pruning algorithm (used in C4.5), and confirms that the 2-norm pruning algorithm is superior in accuracy and speed.

Publication Date

12-1-2007

Publication Title

Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007

Number of Pages

353-358

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

38349112092 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/38349112092

This document is currently not available here.

Share

COinS