Cubist: Rule- And Instance-Based Regression Modeling

Regression modeling using rules with added instance-based corrections.

Version: 0.2.3
Depends: lattice
Imports: reshape2, utils
Suggests: mlbench, caret, knitr, modeldata, dplyr (≥ 0.7.4), rlang, tidyrules
Published: 2020-01-10
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>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
In views: MachineLearning
CRAN checks: Cubist results


Reference manual: Cubist.pdf
Vignettes: Cubist Regresion Models
Package source: Cubist_0.2.3.tar.gz
Windows binaries: r-prerelease:, r-release:, r-oldrel:
macOS binaries: r-prerelease: Cubist_0.2.3.tgz, r-release: Cubist_0.2.3.tgz, r-oldrel: Cubist_0.2.3.tgz
Old sources: Cubist archive

Reverse dependencies:

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


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