caret: plot.train – R documentation

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plot.train

Plot Method for the train Class

Description

This function takes the output of a train object and creates a line or level plot using the lattice or ggplot2 libraries.

Usage

## S3 method for class 'train'
ggplot(
  data = NULL,
  mapping = NULL,
  metric = data$metric[1],
  plotType = "scatter",
  output = "layered",
  nameInStrip = FALSE,
  highlight = FALSE,
  ...,
  environment = NULL
)

## S3 method for class 'train'
plot(
  x,
  plotType = "scatter",
  metric = x$metric[1],
  digits = getOption("digits") - 3,
  xTrans = NULL,
  nameInStrip = FALSE,
  ...
)

Arguments

`data`	an object of class `train`.
`mapping, environment`	unused arguments to make consistent with ggplot2 generic method
`metric`	What measure of performance to plot. Examples of possible values are "RMSE", "Rsquared", "Accuracy" or "Kappa". Other values can be used depending on what metrics have been calculated.
`plotType`	a string describing the type of plot (`"scatter"`, `"level"` or `"line"` (`plot` only))
`output`	either "data", "ggplot" or "layered". The first returns a data frame while the second returns a simple `ggplot` object with no layers. The third value returns a plot with a set of layers.
`nameInStrip`	a logical: if there are more than 2 tuning parameters, should the name and value be included in the panel title?
`highlight`	a logical: if `TRUE`, a diamond is placed around the optimal parameter setting for models using grid search.
`...`	`plot` only: specifications to be passed to `levelplot`, `xyplot`, `stripplot` (for line plots). The function automatically sets some arguments (e.g. axis labels) but passing in values here will over-ride the defaults
`x`	an object of class `train`.
`digits`	an integer specifying the number of significant digits used to label the parameter value.
`xTrans`	a function that will be used to scale the x-axis in scatter plots.

Details

If there are no tuning parameters, or none were varied, an error is produced.

If the model has one tuning parameter with multiple candidate values, a plot is produced showing the profile of the results over the parameter. Also, a plot can be produced if there are multiple tuning parameters but only one is varied.

If there are two tuning parameters with different values, a plot can be produced where a different line is shown for each value of of the other parameter. For three parameters, the same line plot is created within conditioning panels/facets of the other parameter.

Also, with two tuning parameters (with different values), a levelplot (i.e. un-clustered heatmap) can be created. For more than two parameters, this plot is created inside conditioning panels/facets.

Author(s)

Max Kuhn

References

Kuhn (2008), “Building Predictive Models in R Using the caret” (http://www.jstatsoft.org/article/view/v028i05/v28i05.pdf)

Examples

## Not run: 
library(klaR)
rdaFit <- train(Species ~ .,
                data = iris, 
                method = "rda", 
                control = trainControl(method = "cv"))
plot(rdaFit)
plot(rdaFit, plotType = "level")

ggplot(rdaFit) + theme_bw()


## End(Not run)

caret

Classification and Regression Training

v6.0-86

GPL (>= 2)

Authors

Max Kuhn [aut, cre], Jed Wing [ctb], Steve Weston [ctb], Andre Williams [ctb], Chris Keefer [ctb], Allan Engelhardt [ctb], Tony Cooper [ctb], Zachary Mayer [ctb], Brenton Kenkel [ctb], R Core Team [ctb], Michael Benesty [ctb], Reynald Lescarbeau [ctb], Andrew Ziem [ctb], Luca Scrucca [ctb], Yuan Tang [ctb], Can Candan [ctb], Tyler Hunt [ctb]

Initial release