D2MCS: Data Driving Multiple Classifier System

Provides a novel framework to able to automatically develop and deploy an accurate Multiple Classifier System based on the feature-clustering distribution achieved from an input dataset. 'D2MCS' was developed focused on four main aspects: (i) the ability to determine an effective method to evaluate the independence of features, (ii) the identification of the optimal number of feature clusters, (iii) the training and tuning of ML models and (iv) the execution of voting schemes to combine the outputs of each classifier comprising the Multiple Classifier System.

Version: 1.0.0
Depends: R (≥ 4.0)
Imports: caret, devtools, dplyr, FSelector, ggplot2, ggrepel, gridExtra, infotheo, mccr, mltools, ModelMetrics, questionr, recipes, R6, tictoc, varhandle
Suggests: grDevices, knitr, rmarkdown, testthat (≥ 3.0.2)
Published: 2021-05-07
Author: David Ruano-Ordás [aut, ctb], Miguel Ferreiro-Díaz [aut, cre], José Ramón Méndez [aut, ctb], University of Vigo [cph]
Maintainer: Miguel Ferreiro-Díaz <miguel.ferreiro.diaz at gmail.com>
BugReports: https://github.com/drordas/D2MCS/issues
License: GPL-3
URL: https://github.com/drordas/D2MCS
NeedsCompilation: no
Citation: D2MCS citation info
Materials: NEWS
CRAN checks: D2MCS results

Documentation:

Reference manual: D2MCS.pdf
Vignettes: A Brief Introduction to D2MCS

Downloads:

Package source: D2MCS_1.0.0.tar.gz
Windows binaries: r-devel: D2MCS_1.0.0.zip, r-release: D2MCS_1.0.0.zip, r-oldrel: D2MCS_1.0.0.zip
macOS binaries: r-release (arm64): D2MCS_1.0.0.tgz, r-release (x86_64): D2MCS_1.0.0.tgz, r-oldrel: D2MCS_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=D2MCS to link to this page.