Towards a computationally efficient approach to modular classification rule induction

Stahl, F. ORCID: https://orcid.org/0000-0002-4860-0203 and Bramer, M. (2008) Towards a computationally efficient approach to modular classification rule induction. In: Bramer, M., Coenen, F. and Petridis, M. (eds.) Research and Development in Intelligent Systems XXIV. Springer, London, pp. 357-362. ISBN 9781848000933 doi: 10.1007/978-1-84800-094-0_27

Abstract/Summary

Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision Trees (TDIDT) approach. However, alternative approaches have been developed such as the Prism algorithm for inducing modular rules. Prism often produces qualitatively better rules than TDIDT but suffers from higher computational requirements. We investigate approaches that have been developed to minimize the computational requirements of TDIDT, in order to find analogous approaches that could reduce the computational requirements of Prism.