Rule Generation Versus Decision Tree Induction

M.M. Oprea (Romania)

Keywords

machine learning, inductive learning, decision tree induction, rule generation.

Abstract

The success of an expert system depends mainly on the existance of a complete, coherent and non redundant knowledge base. Knowledge base generation can be made by using inductive learning algorithms. The paper presents a comparative study between different inductive learning algorithms, ID3, C4.5, ILA, DCL and RITIO. The main purpose of the study was to identify which class of inductive learning algorithms has a better behaviour, the decision tree based or those not based on decision tree.

Important Links:



Go Back