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Providing equivalent functions for the dummy classifier and regressor used in 'Python' 'scikit-learn' library. Our goal is to allow R users to easily identify baseline performance for their classification and regression problems. Our baseline models use no predictors, and are useful in cases of class imbalance, multiclass classification, and when users want to quickly identify how much improvement their statistical and machine learning models are over several baseline models. We use a "better" default (proportional guessing) for the dummy classifier than the 'Python' implementation ("prior", which is the most frequent class in the training set). The functions in the package can be used on their own, or introduce methods named 'dummy_regressor' or 'dummy_classifier' that can be used within the caret package pipeline.
Version: | 1.1.0 |
Imports: | stats |
Suggests: | caret, knitr, rmarkdown |
Published: | 2023-08-09 |
DOI: | 10.32614/CRAN.package.basemodels |
Author: | Ying-Ju Chen |
Maintainer: | Ying-Ju Chen <ychen4 at udayton.edu> |
License: | MIT + file LICENSE |
URL: | https://github.com/Ying-Ju/basemodels |
NeedsCompilation: | no |
Citation: | basemodels citation info |
Materials: | README |
CRAN checks: | basemodels results |
Reference manual: | basemodels.pdf |
Vignettes: |
Introduction to basemodels |
Package source: | basemodels_1.1.0.tar.gz |
Windows binaries: | r-devel: basemodels_1.1.0.zip, r-release: basemodels_1.1.0.zip, r-oldrel: basemodels_1.1.0.zip |
macOS binaries: | r-release (arm64): basemodels_1.1.0.tgz, r-oldrel (arm64): basemodels_1.1.0.tgz, r-release (x86_64): basemodels_1.1.0.tgz, r-oldrel (x86_64): basemodels_1.1.0.tgz |
Old sources: | basemodels archive |
Please use the canonical form https://CRAN.R-project.org/package=basemodels to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.