Artificial Intelligence Review

, Volume 20, Issue 1, pp 121–141

Relational Case-based Reasoning for Carcinogenic Activity Prediction

  • Eva Armengol
  • Enric Plaza
Article

DOI: 10.1023/A:1026076312419

Cite this article as:
Armengol, E. & Plaza, E. Artificial Intelligence Review (2003) 20: 121. doi:10.1023/A:1026076312419

Abstract

Lazy learning methods are based on retrieving a set of precedent cases similar to a new case. An important issue of these methods is how to estimate the similarity among a new case and the precedents. Usually, similarity measures require that cases have a prepositional representation. In this paper we present Shaud, a similarity measure useful to estimate the similarity among relational cases represented using featureterms. We also present results of the application of Shaud forsolving classification tasks. Specifically we used Shaud for assessingthe carcinogenic activity of chemical compounds in the Toxicology dataset.

feature terms lazy learning methods machine learning similarity assessment toxicology dataset 

Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Eva Armengol
    • 1
  • Enric Plaza
    • 1
  1. 1.Artificial Intelligence Research Institute, Spanish Council for Scientific ResearchCampus UABBellaterra, CataloniaSpain