plotClassProbs

From caret v3.45 by Max Kuhn

Plot Predicted Probabilities in Classification Models

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

Keywords: hplot

Usage

plotClassProbs(object, ...)

Arguments

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"
...: parameters to pass to histogram

Value

A lattice object. Note that the plot has to be printed to be displayed (especially in a loop).

Examples

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",])

Documentation reproduced from package caret, version 3.45, License: GPL-2

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