@@ -3,8 +3,8 @@ Type: Package

 Title: A framework for cross-validated classification problems, with

        applications to differential variability and differential

        distribution testing

-Version: 3.3.4

-Date: 2022-11-22

+Version: 3.3.5

+Date: 2022-11-25

 Authors@R:

     c(

     person(given = "Dario", family = "Strbenac", email = "dario.strbenac@sydney.edu.au", role = c("aut", "cre")),

@@ -22,13 +22,20 @@ randomForestPredictInterface <- function(forest, measurementsTest, ..., returnTy

   if(verbose == 3)

     message("Predicting using random forest.")  

   measurementsTest <- as.data.frame(measurementsTest)

-  classPredictions <- predict(forest, measurementsTest)$predictions

-  classScores <- predict(forest, measurementsTest, predict.all = TRUE)[[1]]

-  classScores <- t(apply(classScores, 1, function(sampleRow) table(factor(classes[sampleRow], levels = classes)) / forest$forest$num.trees))

-  rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest)

-  switch(returnType, class = classPredictions,

-         score = classScores,

-         both = data.frame(class = classPredictions, classScores, check.names = FALSE))

+  

+  predictions <- predict(forest, measurementsTest)

+  if(predictions$treetype == "Classification")

+  {

+    classPredictions <- predictions$predictions

+    classScores <- predict(forest, measurementsTest, predict.all = TRUE)[[1]]

+    classScores <- t(apply(classScores, 1, function(sampleRow) table(factor(classes[sampleRow], levels = classes)) / forest$forest$num.trees))

+    rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest)

+    switch(returnType, class = classPredictions,

+           score = classScores,

+           both = data.frame(class = classPredictions, classScores, check.names = FALSE))

+  } else { # It is "Survival".

+      rowSums(predictions$survival)

+  }

 }

 ################################################################################

@@ -150,6 +150,7 @@ setMethod("performancePlot", "list",

                     }, results, 1:length(results), SIMPLIFY = FALSE))

   plotData <- plotData[, !duplicated(colnames(plotData))]

+  if(length(orderingList) > 0) plotData <- .addUserLevels(plotData, orderingList)

   # Fill in any missing variables needed for ggplot2 code.

   if("fillColour" %in% names(characteristicsList))