confuMat-methods {MLInterfaces} | R Documentation |
This function will compute the confusion matrix for a classifier's output
"classifOutput"
is built on a training subset of the input data. The model is then
used to predict the class of samples in the test set. When the
true class labels for the test set are available the confusion matrix
is the cross-tabulation of the true labels
of the test set against the predictions from the classifier.
type
of confusion matrix desired.
The default is test
, which tabulates classes from the
test set against the associated predictions. If type
is
train
, the training class vector is tabulated against the
predictions on the training set.
library(golubEsets) data(Golub_Merge) smallG <- Golub_Merge[101:150,] k1 <- MLearn(ALL.AML~., smallG, knnI(k=1), 1:30) confuMat(k1) confuMat(k1, "train")