predict.WrappedModel {mlr} | R Documentation |
Predict new data.
Description
Predict the target variable of new data using a fitted model.
What is stored exactly in the (Prediction) object depends
on the predict.type
setting of the Learner.
If predict.type
was set to “prob” probability thresholding
can be done calling the setThreshold function on the
prediction object.
The row names of the input task
or newdata
are preserved in the output.
Usage
## S3 method for class 'WrappedModel'
predict(object, task, newdata, subset = NULL, ...)
Arguments
object |
(WrappedModel) |
task |
(Task) |
newdata |
(data.frame) |
subset |
(integer | logical | |
... |
(any) |
Value
(Prediction).
See Also
Other predict:
asROCRPrediction()
,
getPredictionProbabilities()
,
getPredictionResponse()
,
getPredictionTaskDesc()
,
setPredictThreshold()
,
setPredictType()
Examples
# train and predict
train.set = seq(1, 150, 2)
test.set = seq(2, 150, 2)
model = train("classif.lda", iris.task, subset = train.set)
p = predict(model, newdata = iris, subset = test.set)
print(p)
predict(model, task = iris.task, subset = test.set)
# predict now probabiliies instead of class labels
lrn = makeLearner("classif.lda", predict.type = "prob")
model = train(lrn, iris.task, subset = train.set)
p = predict(model, task = iris.task, subset = test.set)
print(p)
getPredictionProbabilities(p)