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basemodels  

Baseline Models for Classification and Regression
View on CRAN: Click here


Download and install basemodels package within the R console
Install from CRAN:
install.packages("basemodels")

Install from Github:
library("remotes")
install_github("cran/basemodels")

Install by package version:
library("remotes")
install_version("basemodels", "1.1.0")



Attach the package and use:
library("basemodels")
Maintained by
Ying-Ju Chen
[Scholar Profile | Author Map]
First Published: 2023-06-16
Latest Update: 2023-08-09
Description:
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.
How to cite:
Ying-Ju Chen (2023). basemodels: Baseline Models for Classification and Regression. R package version 1.1.0, https://cran.r-project.org/web/packages/basemodels. Accessed 07 May. 2025.
Previous versions and publish date:
1.0.0 (2023-06-16 11:10)
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Complete documentation for basemodels
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