... | ... |
@@ -3,8 +3,8 @@ Type: Package |
3 | 3 |
Title: A framework for cross-validated classification problems, with |
4 | 4 |
applications to differential variability and differential |
5 | 5 |
distribution testing |
6 |
-Version: 3.2.2 |
|
7 |
-Date: 2022-11-22 |
|
6 |
+Version: 3.2.3 |
|
7 |
+Date: 2022-11-25 |
|
8 | 8 |
Author: Dario Strbenac, Ellis Patrick, Sourish Iyengar, Harry Robertson, Andy Tran, John Ormerod, Graham Mann, Jean Yang |
9 | 9 |
Maintainer: Dario Strbenac <dario.strbenac@sydney.edu.au> |
10 | 10 |
VignetteBuilder: knitr |
... | ... |
@@ -22,13 +22,20 @@ randomForestPredictInterface <- function(forest, measurementsTest, ..., returnTy |
22 | 22 |
if(verbose == 3) |
23 | 23 |
message("Predicting using random forest.") |
24 | 24 |
measurementsTest <- as.data.frame(measurementsTest) |
25 |
- classPredictions <- predict(forest, measurementsTest)$predictions |
|
26 |
- classScores <- predict(forest, measurementsTest, predict.all = TRUE)[[1]] |
|
27 |
- classScores <- t(apply(classScores, 1, function(sampleRow) table(factor(classes[sampleRow], levels = classes)) / forest$forest$num.trees)) |
|
28 |
- rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest) |
|
29 |
- switch(returnType, class = classPredictions, |
|
30 |
- score = classScores, |
|
31 |
- both = data.frame(class = classPredictions, classScores, check.names = FALSE)) |
|
25 |
+ |
|
26 |
+ predictions <- predict(forest, measurementsTest) |
|
27 |
+ if(predictions$treetype == "Classification") |
|
28 |
+ { |
|
29 |
+ classPredictions <- predictions$predictions |
|
30 |
+ classScores <- predict(forest, measurementsTest, predict.all = TRUE)[[1]] |
|
31 |
+ classScores <- t(apply(classScores, 1, function(sampleRow) table(factor(classes[sampleRow], levels = classes)) / forest$forest$num.trees)) |
|
32 |
+ rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest) |
|
33 |
+ switch(returnType, class = classPredictions, |
|
34 |
+ score = classScores, |
|
35 |
+ both = data.frame(class = classPredictions, classScores, check.names = FALSE)) |
|
36 |
+ } else { # It is "Survival". |
|
37 |
+ rowSums(predictions$survival) |
|
38 |
+ } |
|
32 | 39 |
} |
33 | 40 |
|
34 | 41 |
################################################################################ |
... | ... |
@@ -150,6 +150,7 @@ setMethod("performancePlot", "list", |
150 | 150 |
}, results, 1:length(results), SIMPLIFY = FALSE)) |
151 | 151 |
|
152 | 152 |
plotData <- plotData[, !duplicated(colnames(plotData))] |
153 |
+ if(length(orderingList) > 0) plotData <- .addUserLevels(plotData, orderingList) |
|
153 | 154 |
|
154 | 155 |
# Fill in any missing variables needed for ggplot2 code. |
155 | 156 |
if("fillColour" %in% names(characteristicsList)) |