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The importance of scaling in data mining for toxicity prediction.

Mazzatorta, P.
; 
Benfenati, E.
; 
Neagu, Daniel
; 
Gini, G.
Publication Date
2002
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Keywords
Data mining, Scaling, QSAR, Qualitative Structure-Activity Relationship, Chemicals toxicity
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Peer-Reviewed
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Accepted for publication
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Engineering and Digital Technology Publications
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Abstract
While mining a data set of 554 chemicals in order to extract information on their toxicity value, we faced the problem of scaling all the data. There are numerous different approaches to this procedure, and in most cases the choice greatly influences the results. The aim of this paper is 2-fold. First, we propose a universal scaling procedure for acute toxicity in fish according to the Directive 92/32/EEC. Second, we look at how expert preprocessing of the data effects the performance of qualitative structure-activity relationship (QSAR) approach to toxicity prediction.
URI
http://hdl.handle.net/10454/3594
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Citation
Mazzatorta, P. Benfenati, E., Neagu, D.C. and Gini, G. (2002). The importance of scaling in data mining for toxicity prediction. Journal of Chemical Information and Computer Sciences. Vol. 4, No. 5, pp. 1250-1255.
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https://doi.org/10.1021/ci025520n
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Article
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