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Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity.
J Cheminform
March 2014
Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Holbeck, Leeds LS11 5PY UK.
Background: A new algorithm has been developed to enable the interpretation of black box models. The developed algorithm is agnostic to learning algorithm and open to all structural based descriptors such as fragments, keys and hashed fingerprints. The algorithm has provided meaningful interpretation of Ames mutagenicity predictions from both random forest and support vector machine models built on a variety of structural fingerprints.
View Article and Find Full Text PDF[Chemical fingerprints--a forensic examination].
Ugeskr Laeger
March 2010
Retsmedicinsk Institut, Aarhus Universitet, DK-8200 Arhus N, Denmark.
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