Prediction objects store the following information:
The row ids of the test set
The corresponding true (observed) response.
The corresponding predicted response.
Additional predictions based on the class and
E.g., the class probabilities for classification or the estimated standard error for regression.
c(..., keep_duplicates = TRUE)
(Prediction, Prediction, ...) -> Prediction
Predictions to a single
FALSE and there are duplicated row ids,
the data of the former passed objects get overwritten by the data of the later passed objects.
Internal data structure.
Set of predict types this object stores.
String in the format
[pkg]::[topic] pointing to a manual page for this object.
NA, but can be set by child classes.
Helper for print outputs.
Opens the corresponding help page referenced by field
Calculates the performance for all provided measures
Task and Learner may be
NULL for most measures, but some measures need to extract information
from these objects.
Note that the
predict_sets of the
measures are ignored by this method,
instead all predictions are used.
Prediction$score( measures = NULL, task = NULL, learner = NULL, train_set = NULL )
The objects of this class are cloneable with this method.
Prediction$clone(deep = FALSE)
Whether to make a deep clone.