xyplot.resamples
From caret v4.39
by Max Kuhn
Lattice Functions for Visualizing Resampling Results
Lattice functions for visualizing resampling results across models
- Keywords
- hplot
Usage
## S3 method for class 'resamples':
xyplot(x, data = NULL, models = x$models[1:2], metric = x$metric[1], ...)
## S3 method for class 'resamples':
densityplot(x, data = NULL, models = x$models, metric = x$metric, ...)
## S3 method for class 'resamples':
bwplot(x, data = NULL, models = x$models, metric = x$metric, ...)
## S3 method for class 'resamples':
splom(x, data = NULL, models = x$models, metric = x$metric[1], ...)
Arguments
- x
- an object generated by
resamples
- data
- Not used
- models
- a character string for which models to plot. Note:
xyplot
requires exactly two models whereas the other methods can plot more than two. - metric
- a character string for which metrics to use as conditioning variables in the plot.
splom
requires exactly one metric and does not condition. - ...
- further arguments to pass to either
histogram
,densityplot
,xyplot
Details
xyplot
only uses two models in the plot. The plot uses difference of the models on the y-axis and the average of the models on the x-axis.
densityplot
and bwplot
display univariate visualizations of the resampling distributions while splom
shows the pair-wise relationships.
Value
- a lattice object
See Also
Examples
#load(url("http://caret.r-forge.r-project.org/Classification_and_Regression_Training_files/exampleModels.RData"))
resamps <- resamples(list(CART = rpartFit,
CondInfTree = ctreeFit,
MARS = earthFit))
bwplot(resamps,
metric = "RMSE")
densityplot(resamps,
auto.key = list(columns = 3),
pch = "|")
xyplot(resamps,
models = c("CART", "MARS"),
metric = "RMSE")
splom(resamps, metric = "RMSE")
Community examples
Looks like there are no examples yet.