predict.dbcsp {dbcsp} | R Documentation |
Predict function implemented by dbcsp class
Description
This function returns the labels predicted for the input instances. If true_targets
are passed as parameter,
the accuracy obtained is printed too.
Usage
## S3 method for class 'dbcsp'
predict(object, X_test, true_targets=NULL, ...)
Arguments
object |
object of class |
X_test |
list of matrices for test data. |
true_targets |
vector of true labels of the instances. Note that they must match the names of the labels used when training the model. |
... |
not currently used. |
Details
It gives the predictions for the test data using the model saved in the object, which has been previously trained with
the train.dbcsp
function. If the true_targets
are indicated, the confusion matrix and obtained accuracy value are
returned too.
Value
The values returned by the LDA predict
function, a list with these components:
-
class
The MAP classification (a factor) -
posterior
Posterior probabilities for the classes -
x
The scores of test cases on up to dimen discriminant variables
If the true_targets
are indicated, two more items are added to the output list:
-
confusion_matrix
The confusion matrix obtained with predicted labels and true labels. -
acc
The accuracy value obtained for the test instances.
See Also
dbcsp
, print
, summary
, train
, selectQ
, plot
, boxplot
Examples
# Read data from 2 classes
x <- AR.data$come[1:20]
y <- AR.data$five[1:20]
mydbcsp <- new("dbcsp", X1 = x, X2 = y)
mydbcsp <- train(mydbcsp,fold=3)
test_data <- c(AR.data$come[20:24], AR.data$five[20:24])
test_labels <- c(rep('x',5),rep('y',5))
predictions <- predict(mydbcsp,test_data,test_labels)
# Predicted classes
print(predictions$class)
# Confusion matrix
print(predictions$confusion_matrix)
# Accuracy
print(predictions$acc)