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 |
|
---|---|
Author | Ying-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>) |
Maintainer | Ying-Ju Chen <ychen4@udayton.edu> |
License | MIT + file LICENSE |
Version | 1.1.0 |
URL | https://github.com/Ying-Ju/basemodels |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.