Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity-Reference-Cited by-同舟云学术

Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity

Published:2014-03-25 Issue:1 Volume:6 Page:
ISSN:1758-2946
Container-title:Journal of Cheminformatics
language:en
Short-container-title:J Cheminform

Author:

Webb Samuel J,Hanser Thierry,Howlin Brendan,Krause Paul,Vessey Jonathan D

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Link

http://link.springer.com/article/10.1186/1758-2946-6-8/fulltext.html

Reference41 articles.

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3. Garcia-Borroto M, Martinez-Trinidad JF, Carrasco-Ochoa JA: A New emerging pattern mining algorithm and its application in supervised classification. Proceedings Pacific-Asia conference on knowledge discovery and data mining. Edited by: Zaki MJ, Jeffrey XY, Ravindran B, Pudi V. 2010, Berlin Heidelberg: Springer, 150-157.

4. Ferrari T, Cattaneo D, Gini G, Golbamaki Bakhtyari N, Manganaro A, Benfenati E: Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction. SAR QSAR Environ Res. 2013, 24: 631-649.

5. Bacha PA, Gruver HS, Den Hartog BK, Tamura SY, Nutt RF: Rule extraction from a mutagenicity data set using adaptively grown phylogenetic-like trees. J Chem Inf Comput Sci. 2002, 42: 1104-1111.

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