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:	2.0.0
Depends:	R (≥ 3.6.0)
Imports:	KernSmooth, MSQC, class (≥ 7.3.14), e1071 (≥ 1.6.7), elasticnet (≥ 1.1), 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, methods
Suggests:	knitr, rmarkdown, testthat, vdiffr (≥ 0.3.0)
Published:	2022-05-01
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
Materials:	NEWS
CRAN checks:	chemmodlab results

Documentation:

Reference manual:

chemmodlab.pdf

Downloads:

Package source:	chemmodlab_2.0.0.tar.gz
Windows binaries:	r-devel: chemmodlab_2.0.0.zip, r-release: chemmodlab_2.0.0.zip, r-oldrel: chemmodlab_2.0.0.zip
macOS binaries:	r-release (arm64): chemmodlab_2.0.0.tgz, r-oldrel (arm64): chemmodlab_2.0.0.tgz, r-release (x86_64): chemmodlab_2.0.0.tgz, r-oldrel (x86_64): chemmodlab_2.0.0.tgz
Old sources:	chemmodlab archive

Linking:

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