| 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",])