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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.
Documentation:
Downloads:
Linking:
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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.
[aut, cre],
Fadel M. Megahed