ggplot.train

From caret v6.0-86 by Max Kuhn

Plot Method for the train Class

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

Keywords: hplot

Usage

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

References

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

Examples

# NOT RUN {

# }
# 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()

# }
# NOT RUN {
 
# }

Documentation reproduced from package caret, version 6.0-86, License: GPL (>= 2)

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