@@ -3,9 +3,9 @@ Type: Package

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

        applications to differential variability and differential

        distribution testing

-Version: 3.3.2

-Date: 2022-11-09

-Authors@R: 

+Version: 3.3.3

+Date: 2022-11-17

+Authors@R:

     c(

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

     person(given = "Ellis", family = "Patrick", role = "aut"),

@@ -6,9 +6,11 @@ randomForestTrainInterface <- function(measurementsTrain, outcomeTrain, mTryProp

   if(verbose == 3)

     message("Fitting random forest classifier to training data.")

   mtry <- round(mTryProportion * ncol(measurementsTrain)) # Number of features to try.

-      

   # Convert to base data.frame as randomForest doesn't understand DataFrame.

-  ranger::ranger(x = as(measurementsTrain, "data.frame"), y = outcomeTrain, mtry = mtry, importance = "impurity_corrected", ...)

+  fittedModel <- ranger::ranger(x = as(measurementsTrain, "data.frame"), y = outcomeTrain, mtry = mtry, ...)

+  forImportance <- ranger::ranger(x = as(measurementsTrain, "data.frame"), y = outcomeTrain, mtry = mtry, importance = "impurity_corrected", ...)

+  attr(fittedModel, "forImportance") <- forImportance

+  fittedModel

 }

 attr(randomForestTrainInterface, "name") <- "randomForestTrainInterface"

@@ -37,7 +39,8 @@ randomForestPredictInterface <- function(forest, measurementsTest, ..., returnTy

 forestFeatures <- function(forest)

                   {

-                    rankedFeaturesIndices <- order(ranger::importance(forest), decreasing = TRUE)

-                    selectedFeaturesIndices <- which(ranger::importance(forest) > 0)

+                    forImportance <- attr(forest, "forImportance")

+                    rankedFeaturesIndices <- order(ranger::importance(forImportance), decreasing = TRUE)

+                    selectedFeaturesIndices <- which(ranger::importance(forImportance) > 0)

                     list(rankedFeaturesIndices, selectedFeaturesIndices)

                   }

\ No newline at end of file

@@ -44,6 +44,8 @@

 #' @param legendSize The size of the boxes in the legends.

 #' @param plot Logical. IF \code{TRUE}, a plot is produced on the current

 #' graphics device.

+#' @param ... Parameters not used by the \code{ClassifyResult} method that does

+#' list-packaging but used by the main \code{list} method.

 #' @return A plot is produced and a grob is returned that can be saved to a

 #' graphics device.

 #' @author Dario Strbenac

@@ -7,6 +7,7 @@

 \alias{calcExternalPerformance,factor,factor-method}

 \alias{calcExternalPerformance,Surv,numeric-method}

 \alias{calcCVperformance,ClassifyResult-method}

+\alias{calcExternalPerformance,factor,tabular-method}

 \title{Add Performance Calculations to a ClassifyResult Object or Calculate for a

 Pair of Factor Vectors}

 \usage{

@@ -24,6 +25,12 @@ Pair of Factor Vectors}

   performanceType = "C-index"

 )

+\S4method{calcExternalPerformance}{factor,tabular}(

+  actualOutcome,

+  predictedOutcome,

+  performanceType = "AUC"

+)

+

 \S4method{calcCVperformance}{ClassifyResult}(

   result,

   performanceType = c("Balanced Accuracy", "Balanced Error", "Error", "Accuracy",

@@ -58,6 +58,9 @@

 \item{results}{A list of \code{\link{ClassifyResult}} objects. Could also be

 a matrix of pre-calculated metrics, for backwards compatibility.}

+\item{...}{Parameters not used by the \code{ClassifyResult} method that does

+list-packaging but used by the main \code{list} method.}

+

 \item{comparison}{Default: "auto". The aspect of the experimental

 design to compare. Can be any characteristic that all results share.}