COPYRIGHT YEAR

1998

AUTHORS

Ross D. King

TITLE

Application of Machine Learning in Drug Design

ABSTRACT

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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1 book-chapters:7bd3e64f2028e554a630846df186d4a3 sg:abstract 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.
2 sg:abstractRights OpenAccess
3 sg:bibliographyRights Restricted
4 sg:bodyHtmlRights Restricted
5 sg:bodyPdfRights Restricted
6 sg:copyrightHolder Springer Science+Business Media Dordrecht
7 sg:copyrightYear 1998
8 sg:ddsId Chap5
9 sg:doi 10.1007/978-94-015-9028-0_5
10 sg:esmRights OpenAccess
11 sg:hasBook books:edd23a3cb557b5dbecbf567793711da5
12 sg:hasBookEdition book-editions:62ca67613056601b358409213eede030
13 sg:hasContribution contributions:b178ed82073cfdd0c80663a7491c5492
14 sg:language En
15 sg:license http://scigraph.springernature.com/explorer/license/
16 sg:metadataRights OpenAccess
17 sg:pageFirst 53
18 sg:pageLast 63
19 sg:scigraphId 7bd3e64f2028e554a630846df186d4a3
20 sg:title Application of Machine Learning in Drug Design
21 sg:webpage https://link.springer.com/10.1007/978-94-015-9028-0_5
22 rdf:type sg:BookChapter
23 rdfs:label BookChapter: Application of Machine Learning in Drug Design
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