chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models

Contains a set of methods for fitting models and methods for validating the resulting models. The statistical methodologies comprise a comprehensive collection of approaches whose validity and utility have been accepted by experts in the Cheminformatics field. As promising new methodologies emerge from the statistical and data-mining communities, they will be incorporated into the laboratory. These methods are aimed at discovering quantitative structure-activity relationships (QSARs). However, the user can directly input their own choices of descriptors and responses, so the capability for comparing models is effectively unlimited.

Version: 1.0.0
Depends: R (≥ 3.1.1)
Imports: class (≥ 7.3.14), e1071 (≥ 1.6.7), elasticnet (≥ 1.1), foreach (≥ 1.4.3), lars (≥ 1.2), MASS (≥ 7.3.45), nnet (≥ 7.3.12), pROC (≥ 1.8), randomForest (≥ 4.6.12), rpart (≥ 4.1.10), tree (≥ 1.0.37), pls (≥ 2.5.0), caret (≥ 6.0-71), stats, graphics, grDevices, utils, datasets, methods
Suggests: knitr, rmarkdown
Published: 2017-04-21
Author: Jacqueline Hughes-Oliver [aut], Jeremy Ash [aut, cre], Atina Brooks [aut]
Maintainer: Jeremy Ash <jrash at ncsu.edu>
BugReports: https://github.com/jrash/ChemModLab/issues
License: GPL-3
URL: https://github.com/jrash/ChemModLab
NeedsCompilation: no
CRAN checks: chemmodlab results

Downloads:

Reference manual: chemmodlab.pdf
Package source: chemmodlab_1.0.0.tar.gz
Windows binaries: r-devel: chemmodlab_1.0.0.zip, r-release: chemmodlab_1.0.0.zip, r-oldrel: chemmodlab_1.0.0.zip
OS X binaries: r-release: chemmodlab_1.0.0.tgz, r-oldrel: chemmodlab_1.0.0.tgz

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