varimp.pmforest: Variable Importance for pmforest

In model4you: Stratified and Personalised Models Based on Model-Based Trees and Forests

Description

See varimp.cforest.

Usage

## S3 method for class 'pmforest'
varimp(
  object,
  nperm = 1L,
  OOB = TRUE,
  risk = function(x, ...) -objfun(x, sum = TRUE, ...),
  conditional = FALSE,
  threshold = 0.2,
  ...
)

Arguments

object	DESCRIPTION.
nperm	the number of permutations performed.
OOB	a logical determining whether the importance is computed from the out-of-bag sample or the learning sample (not suggested).
risk	the risk to be evaluated. By default the objective function (e.g. log-Likelihood) is used.
conditional	a logical determining whether unconditional or conditional computation of the importance is performed.
threshold	the value of the test statistic or 1 - p-value of the association between the variable of interest and a covariate that must be exceeded inorder to include the covariate in the conditioning scheme for the variable of interest (only relevant if conditional = TRUE).
...	passed on to objfun.

Value

A vector of 'mean decrease in accuracy' importance scores.

model4you documentation built on Jan. 20, 2021, 5:09 p.m.