plotClassProbs {caret} | R Documentation |
This function takes an object (preferably from the function extractProb
)
and creates a lattice plot.
If the call to extractProb
included test data, these data are shown, but
if unknowns were also included, these are not plotted
plotClassProbs(object, ...)
object |
an object (preferably from the function extractProb . There
should be columns for each level of the class factor and columns named obs , pred , model (e.g. "rpart", "nnet" etc)
and dataType (e.g. "Training", "Test" etc) |
... |
parameters to pass to histogram |
A lattice object. Note that the plot has to be printed to be displayed (especially in a loop).
Max Kuhn
data(iris) set.seed(90) inTrain <- sample(1:dim(iris)[1], 100) trainData <- iris[inTrain,] testData <- iris[-inTrain,] rpartFit <- train(trainData[, -5], trainData[, 5], "rpart", tuneLength = 15) ldaFit <- train(trainData[, -5], trainData[, 5], "lda") predProbs <- extractProb(list(ldaFit, rpartFit), testX = testData[, -5], testY = testData[, 5]) plotClassProbs(predProbs) plotClassProbs(predProbs[predProbs$model == "lda",]) plotClassProbs(predProbs[predProbs$model == "lda" & predProbs$dataType == "Test",])