select_features: Select features

In messamat/globalIRmap: What the Package Does (One Line, Title Case)

Description

Select a subset of model predictor variables (aka features) based on variable importance p-value.

Usage

select_features(in_bm, in_lrnid, in_task, pcutoff, inp_resdir = NULL)

Arguments

in_bm	BenchmarkResult containing the ResampleResult for the learner of interest, based on which to select predictor variables. Can also be name of serialized file (.qs) on disk (accessed through qread) containing BenchmarkResult object.
in_lrnid	id of learner to extract from BenchmarkResult (e.g., "oversample.classif.ranger")
in_task	Task containing predictor variables to subset
pcutoff	variable p-value cut-off under which to select variable, see extract_impperf_nestedrf and importance_pvalues for more information on p-value calculation.
inp_resdir	(character) path to where qs file is located (excluding the name of the qs file)

Value

list containing the original in_task and the updated task only included selected predictor variables.

messamat/globalIRmap documentation built on July 4, 2021, 10:48 a.m.