In:
Water Quality Research Journal, IWA Publishing, Vol. 33, No. 1 ( 1998-02-01), p. 153-166
Kurzfassung:
We investigated the connection between the data preprocessing strategy and kernel choice on the quality of the associated basic probabilistic neural network models for the acute toxicity of various chemicals to the fathead minnow and to Vibrio fischeri bacteria. The models employ exclusively structural parameters and physicochemical properties as inputs. Results show that the Gaussian kernel is preferable over the reciprocal kernel model. Data preprocessing based on the hyperbolic tangent and the sigmoid logistic transforms provides the best results at the level of the cross validation experiment. Improved models based on cross validation partial models and linear corrections were also investigated. The results show that the improved models with data preprocessing based on the hyperbolic tangent and the finite interval transforms are the best with practically identical quality of predictions.
Materialart:
Online-Ressource
ISSN:
1201-3080
,
2408-9443
DOI:
10.2166/wqrj.1998.009
Sprache:
Englisch
Verlag:
IWA Publishing
Publikationsdatum:
1998
ZDB Id:
2948758-4
ZDB Id:
2739923-0
SSG:
12