ranking {projpred}

Predictor ranking(s)

Description

Extracts the predictor ranking(s) from an object of class vsel (returned by varsel() or cv_varsel()). A predictor ranking is simply a character vector of predictor terms ranked by predictive relevance (with the most relevant term first). In any case, objects of class vsel contain the predictor ranking based on the full-data search. If an object of class vsel is based on a cross-validation (CV) with fold-wise searches (i.e., if it was created by cv_varsel() with validate_search = TRUE), then it also contains fold-wise predictor rankings.

Usage

ranking(object, ...)

## S3 method for class 'vsel'
ranking(object, nterms_max = NULL, ...)

Arguments

object

The object from which to retrieve the predictor ranking(s). Possible classes may be inferred from the names of the corresponding methods (see also the description).

...

Currently ignored.

nterms_max

Maximum submodel size (number of predictor terms) for the predictor ranking(s), i.e., the submodel size at which to cut off the predictor ranking(s). Using NULL is effectively the same as setting nterms_max to the full model size, i.e., this means to not cut off the predictor ranking(s) at all. Note that nterms_max does not count the intercept, so nterms_max = 1 corresponds to the submodel consisting of the first (non-intercept) predictor term.

Value

An object of class ranking which is a list with the following elements:

• fulldata: The predictor ranking from the full-data search.

• foldwise: The predictor rankings from the fold-wise searches in the form of a character matrix (only available if object is based on a CV with fold-wise searches, otherwise element foldwise is NULL). The rows of this matrix correspond to the CV folds and the columns to the submodel sizes. Each row contains the predictor ranking from the search of that CV fold.

See Also

cv_proportions()

Examples

# For an example, see `?plot.cv_proportions`.