Application of Neural Networks in the QSAR Analysis of Percent Effect Biological Data: Comparison with Adaptive Least Squares and Nonlinear Regression Analysis
- 1 August 1993
- journal article
- research article
- Published by Taylor & Francis in SAR and QSAR in Environmental Research
- Vol. 1 (2-3) , 137-152
- https://doi.org/10.1080/10629369308028825
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 physico-chemical descriptors.Keywords
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