basemodels: Baseline Models for Classification and Regression

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.

Package details

AuthorYing-Ju Chen [aut, cre] (<https://orcid.org/0000-0002-6444-6859>), Fadel M. Megahed [aut] (<https://orcid.org/0000-0003-2194-5110>), L. Allison Jones-Farmer [aut] (<https://orcid.org/0000-0002-1529-1133>), Steven E. Rigdon [aut] (<https://orcid.org/0000-0001-7668-0899>)
MaintainerYing-Ju Chen <ychen4@udayton.edu>
LicenseMIT + file LICENSE
Version1.1.0
URL https://github.com/Ying-Ju/basemodels
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("basemodels")

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basemodels documentation built on Aug. 9, 2023, 9:09 a.m.