Summary
Neural networks and machine learning are two methods that are increasingly being used to model Structure Activity Relationships (SARs). These new methods make few statistical assumptions and are non-linear and nonparametric. We describe back-propagation from the field of neural networks, and Progol from machine learning, and illustrate their learning mechanisms using a simple expository problem.
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© 1998 Springer Science+Business Media Dordrecht
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King, R.D. (1998). Application of Machine Learning in Drug Design. In: Codding, P.W. (eds) Structure-Based Drug Design. NATO ASI Series, vol 352. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9028-0_5
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DOI: https://doi.org/10.1007/978-94-015-9028-0_5
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