orsf_vs: Variable selection

In aorsf: Accelerated Oblique Random Survival Forests

Variable selection

Description

Variable selection

Usage

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

Arguments

object	(orsf_fit) a trained oblique random survival forest (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?

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.

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

Examples

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

orsf_vs(object, n_predictor_min = 17)

aorsf documentation built on Oct. 26, 2023, 5:08 p.m.