marginal_vimp_: Internal function for use by calculate_marginal_vimp

In breather/brightbox: Peek into any blackbox learner (including ensembles)

Description

Calculate the change in error from baseline model when removing a variable from training data.

Usage

marginal_vimp_(var, method, x, y, resampling_indices, tuneGrid, trControl,
  loss_metric, base_resample_dt, ...)

Arguments

var	character. variable to remove from training data in order to obtain importance of that variable.
method	character string defining method to pass to caret
x	data.table containing predictor variables
y	vector containing target variable
resampling_indices	a list of integer vectors corresponding to the row indices used for each resampling iteration
tuneGrid	a data.frame containing hyperparameter values for caret. Should only contain one value for each hyperparameter. Set to NULL if caret method does not have any hyperparameter values.
trControl	trainControl object to be passed to caret train.
loss_metric	character. Loss metric to evaluate accuracy of model
base_resample_dt	"resample" data.frame from caret model object returned from baseline model
...	additional arguments to pass to caret train

breather/brightbox documentation built on May 13, 2019, 5:04 a.m.