Prediction Object for Regression
This object wraps the predictions returned by a learner of class LearnerRegr, i.e. the predicted response and standard error. Additionally, probability distributions implemented in distr6 are supported.
mlr3::Prediction -> PredictionRegr
response(numeric())
Access the stored predicted response.
se(numeric())
Access the stored standard error.
distr(distr6::VectorDistribution)
Access the stored vector distribution.
Requires package distr6.
new()
Creates a new instance of this R6 class.
PredictionRegr$new( task = NULL, row_ids = task$row_ids, truth = task$truth(), response = NULL, se = NULL, distr = NULL, check = TRUE )
task(TaskRegr)
Task, used to extract defaults for row_ids and truth.
row_ids(integer())
Row ids of the predicted observations, i.e. the row ids of the test set.
truth(numeric())
True (observed) response.
response(numeric())
Vector of numeric response values.
One element for each observation in the test set.
se(numeric())
Numeric vector of predicted standard errors.
One element for each observation in the test set.
distr(distr6::VectorDistribution)
VectorDistribution from distr6.
Each individual distribution in the vector represents the random variable 'survival time'
for an individual observation.
check(logical(1))
If TRUE, performs some argument checks and predict type conversions.
Other Prediction:
PredictionClassif,
Prediction
task = tsk("boston_housing")
learner = lrn("regr.featureless", predict_type = "se")
p = learner$train(task)$predict(task)
p$predict_types
head(as.data.table(p))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.