... | ... |
@@ -10,6 +10,6 @@ kNNinterface <- function(measurementsTrain, classesTrain, measurementsTest, ..., |
10 | 10 |
if(verbose == 3) |
11 | 11 |
message("Fitting k Nearest Neighbours classifier to data and predicting classes.") |
12 | 12 |
|
13 |
- class::knn(as.matrix(measurementsTrain), as.matrix(measurementsTest), classesTrain, ...) |
|
13 |
+ setNames(class::knn(as.matrix(measurementsTrain), as.matrix(measurementsTest), classesTrain, ...), rownames(measurementsTest)) |
|
14 | 14 |
} |
15 | 15 |
attr(kNNinterface, "name") <- "kNNinterface" |
... | ... |
@@ -149,12 +149,14 @@ mixModelsPredict <- function(models, measurementsTest, difference = c("unweighte |
149 | 149 |
classScores <- classScores / sum(classScores) # Make different feature selection sizes comparable. |
150 | 150 |
classPredicted <- names(classScores)[which.max(classScores)] |
151 | 151 |
} |
152 |
- |
|
153 | 152 |
data.frame(class = factor(classPredicted, levels = classesNames), t(classScores), check.names = FALSE) |
154 | 153 |
})) |
155 | 154 |
|
156 |
- switch(returnType, class = predictions[, "class"], |
|
157 |
- score = predictions[, colnames(predictions) %in% classesNames], |
|
155 |
+ classPredictions <- predictions[, "class"] |
|
156 |
+ classScores <- predictions[, colnames(predictions) %in% classesNames] |
|
157 |
+ rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest) |
|
158 |
+ switch(returnType, class = classPredictions, |
|
159 |
+ score = classScores, |
|
158 | 160 |
both = data.frame(class = predictions[, "class"], predictions[, colnames(predictions) %in% classesNames, drop = FALSE], check.names = FALSE) |
159 | 161 |
) |
160 | 162 |
} |
... | ... |
@@ -115,9 +115,12 @@ naiveBayesKernel <- function(measurementsTrain, classesTrain, measurementsTest, |
115 | 115 |
|
116 | 116 |
data.frame(class = factor(classPredicted, levels = levels(classesTrain)), t(classScores), check.names = FALSE) |
117 | 117 |
})) |
118 |
- |
|
119 |
- switch(returnType, class = predictions[, "class"], |
|
120 |
- score = predictions[, 2:ncol(predictions)], |
|
118 |
+ |
|
119 |
+ classPredictions <- predictions[, "class"] |
|
120 |
+ classScores <- predictions[, 2:ncol(predictions)] |
|
121 |
+ rownames(classScores) <- names(classPredictions) <- rownames(measurementsTest) |
|
122 |
+ switch(returnType, class = classPredictions, |
|
123 |
+ score = classScores, |
|
121 | 124 |
both = predictions) |
122 | 125 |
} |
123 | 126 |
attr(naiveBayesKernel, "name") <- "naiveBayesKernel" |
124 | 127 |
\ No newline at end of file |