autoplot.caretStack: Convenience function for more in-depth diagnostic plots of...

In caretEnsemble: Ensembles of Caret Models

Convenience function for more in-depth diagnostic plots of caretStack objects

Description

This function provides a more robust series of diagnostic plots for a caretEnsemble object.

Usage

## S3 method for class 'caretStack'
autoplot(object, training_data = NULL, xvars = NULL, show_class_id = 2L, ...)

Arguments

object	a caretStack object
training_data	The data used to train the ensemble. Required if xvars is not NULL Must be in the same row order as when the models were trained.
xvars	a vector of the names of x variables to plot against residuals
show_class_id	For classification only: which class level to show on the plot
...	ignored

Value

A grid of diagnostic plots. Top left is the range of the performance metric across each component model along with its standard deviation. Top right is the residuals from the ensembled model plotted against fitted values. Middle left is a bar graph of the weights of the component models. Middle right is the disagreement in the residuals of the component models (unweighted) across the fitted values. Bottom left and bottom right are the plots of the residuals against two random or user specified variables. Note that the ensemble must have been trained with savePredictions = "final", which is required to get residuals from the stack for the plot.

Examples

set.seed(42)
data(models.reg)
ens <- caretStack(models.reg[1:2], method = "lm")
autoplot(ens)

caretEnsemble documentation built on Sept. 13, 2024, 1:11 a.m.