Application of neural networks in the QSAR analysis of percent effect biological data: comparison with adaptive least squares and nonlinear regression analysis.

Abstract:

:Artificial neural networks (ANN) can be used for the direct QSAR analysis of percent effect biological data, thus avoiding the bias introduced by arbitrarily chosen classes and the loss of information due to prior classification. For two data sets the ANN results are compared with those obtained by adaptive least squares and nonlinear regression analyses. In comparison with the other methods the neural network shows higher predictive power and does not require an explicit equation relating the observed effect to physicochemical descriptors.

journal_name

SAR QSAR Environ Res

authors

Wiese M,Schaper KJ

doi

10.1080/10629369308028825

subject

Has Abstract

pub_date

1993-01-01 00:00:00

pages

137-52

issue

2-3

eissn

1062-936X

issn

1029-046X

journal_volume

1

pub_type

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