Clustering and classification techniques to assess aquatic toxicity

Giuseppina Gini, Emilio Benfenati, Daniel Boley

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The goal of toxicity, prediction is to describe the relationship between chemical properties, on the one hand, and biological and toxicological processes, on the other. Knowledge about the causes of toxicity is incomplete. No single property can satisfy the requirement to model the toxic activity. In the present study we consider different methods to build up models useful for aquatic toxicity prediction. Our study is in the tradition of SAR and QSAR methods, but tries to predict a category. Due to the variability of the toxicity phenomenon, classification methods may present advantages because they refer to intervals of the observed toxic effect. Furthermore classification of compounds according to their toxicity has direct application for regulation of chemicals. In the paper we will report results obtained from the preparation and study of a data set of different classes of chemicals; starting from recursive partitioning algorithms we will test their results against clustering and classifiers.

Original languageEnglish
Title of host publicationInternational Conference on Knowledge-Based Intelligent Electronic Systems, Proceedings, KES
PublisherIEEE
Pages166-172
Number of pages7
Volume1
Publication statusPublished - 2000
Event4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies (KES'2000) - Brighton, UK
Duration: Aug 30 2000Sep 1 2000

Other

Other4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies (KES'2000)
CityBrighton, UK
Period8/30/009/1/00

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Clustering and classification techniques to assess aquatic toxicity'. Together they form a unique fingerprint.

Cite this