Cubist: Rule- And Instance-Based Regression Modeling

Regression modeling using rules with added instance-based corrections.

Version: 0.3.0
Depends: lattice
Imports: reshape2, utils
Suggests: mlbench, knitr, modeldata, dplyr (≥ 0.7.4), rlang, tidyrules, rmarkdown
Published: 2021-05-28
Author: Max Kuhn [aut, cre], Steve Weston [ctb], Chris Keefer [ctb], Nathan Coulter [ctb], Ross Quinlan [aut] (Author of imported C code), Rulequest Research Pty Ltd. [cph] (Copyright holder of imported C code)
Maintainer: Max Kuhn <mxkuhn at gmail.com>
BugReports: https://github.com/topepo/Cubist/issues
License: GPL-3
URL: https://topepo.github.io/Cubist//, https://topepo.github.io/Cubist/
NeedsCompilation: yes
Materials: NEWS
In views: MachineLearning
CRAN checks: Cubist results

Documentation:

Reference manual: Cubist.pdf
Vignettes: Cubist Regresion Models

Downloads:

Package source: Cubist_0.3.0.tar.gz
Windows binaries: r-devel: Cubist_0.3.0.zip, r-devel-UCRT: Cubist_0.3.0.zip, r-release: Cubist_0.3.0.zip, r-oldrel: Cubist_0.3.0.zip
macOS binaries: r-release (arm64): Cubist_0.3.0.tgz, r-release (x86_64): Cubist_0.3.0.tgz, r-oldrel: Cubist_0.3.0.tgz
Old sources: Cubist archive

Reverse dependencies:

Reverse imports: C50, dendroTools, LDLcalc, rminer, soilassessment, tsensembler
Reverse suggests: caret, dissever, fscaret, imputeR, mlr, pdp, rules, tidypredict, tidyrules, vip

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