resamples
Collation and Visualization of Resampling Results
These functions provide methods for collection, analyzing and visualizing a set of resampling results from a common data set.
- Keywords
- models
Usage
resamples(x, ...)## S3 method for class 'default':
resamples(x, modelNames = names(x), ...)
## S3 method for class 'resamples':
summary(object, ...)
Arguments
Details
The results from train
can have more than one performance metric per resample. Each metric in the input object is saved.
resamples
checks that the resampling results match; that is, the indices in the object trainObject$control$index
are the same. Also, the argument trainControl
returnResamp
should have a value of "final"
for each model.
The summary function computes summary statistics across each model/metric combination.
Value
- An object with class
"resamples"
with elements call the call values a data frame of results where rows correspond to resampled data sets and columns indicate the model and metric models a character string of model labels metrics a character string of performance metrics methods a character string of the train
method
argument values for each model
See Also
train
, trainControl
, diff.resamples
, xyplot.resamples
, densityplot.resamples
, bwplot.resamples
, splom.resamples
Examples
data(BloodBrain)
set.seed(1)
tmp <- createDataPartition(logBBB,
p = .8,
times = 100)
rpartFit <- train(bbbDescr, logBBB,
"rpart",
tuneLength = 16,
trControl = trainControl(
method = "LGOCV", index = tmp))
ctreeFit <- train(bbbDescr, logBBB,
"ctree",
trControl = trainControl(
method = "LGOCV", index = tmp))
earthFit <- train(bbbDescr, logBBB,
"earth",
tuneLength = 20,
trControl = trainControl(
method = "LGOCV", index = tmp))
## or load pre-calculated results using:
## 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))
resamps
summary(resamps)