ggplot.train | R Documentation |
This function takes the output of a train
object and creates a
line or level plot using the lattice or ggplot2 libraries.
## 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,
...
)
data |
an object of class |
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 ( |
output |
either "data", "ggplot" or "layered". The first returns a data
frame while the second returns a simple |
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 |
... |
|
x |
an object of class |
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. |
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.
Max Kuhn
Kuhn (2008), “Building Predictive Models in R Using the caret” (\Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v028.i05")})
train
, levelplot
,
xyplot
, stripplot
,
ggplot
## 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)
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