exprso package includes these feature selection modules:
Considering the high-dimensionality of many datasets, it is prudent and
often necessary to prioritize which features to include during model
construction. This package provides functions for some of the most frequently
used feature selection methods. Each function works as a self-contained wrapper
that (1) pre-processes the
ExprsArray input, (2) performs the feature
selection, and (3) returns an
ExprsArray output with an updated feature
selection history. These histories get passed along at every step of the way
until they eventually get used to pre-process an unlabeled dataset during
model deployment (i.e., prediction).
top specifies either the names or the number of features
to supply TO the feature selection method, not what the user intends to
retrieve FROM the feature selection method. When calling the first feature
selection method (or the first build method, if skipping feature selection),
top argument will select a "top ranked" feature set according
to their default order in the
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