ggplot.train {caret} | R Documentation

## 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.
`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.
`...` | `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

### 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)

### See Also

`train`, `levelplot`, `xyplot`, `stripplot`, `ggplot`

### 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)

[Package caret version 6.0-73 Index]