Skip to contents

Variable selection

Source: R/orsf_vs.R
orsf_vs.Rd

Variable selection

Usage

orsf_vs(object, n_predictor_min = 3, verbose_progress = FALSE)

Arguments

object

(ObliqueForest) a trained oblique random forest object (see orsf).

n_predictor_min

(integer) the minimum number of predictors allowed

verbose_progress

(logical) not implemented yet. Should progress be printed to the console?

Value

a data.table with four columns:

  • n_predictors: the number of predictors used

  • stat_value: the out-of-bag statistic

  • predictors_included: the names of the predictors included

  • predictor_dropped: the predictor selected to be dropped

Details

tree_seeds should be specified in object so that each successive run of orsf will be evaluated in the same out-of-bag samples as the initial run.

Examples


object <- orsf(formula = time + status ~ .,
               data = pbc_orsf,
               n_tree = 25,
               importance = 'anova')

orsf_vs(object, n_predictor_min = 15)
#>    n_predictors stat_value                             predictors_included
#> 1:           15  0.8474921   id,age,sex_f,ascites_1,hepato_1,spiders_1,...
#> 2:           16  0.8322308   id,age,sex_f,ascites_1,hepato_1,spiders_1,...
#> 3:           17  0.8125944   id,age,sex_f,ascites_1,hepato_1,spiders_1,...
#> 4:           18  0.8221782 id,trt_placebo,age,sex_f,ascites_1,hepato_1,...
#>    predictor_dropped
#> 1:                id
#> 2:              trig
#> 3:          platelet
#> 4:       trt_placebo