Abstract Prediction Object
This is the abstract base class for task objects like PredictionClassif or PredictionRegr.
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 predict_type.
E.g., the class probabilities for classification or the estimated standard error for regression.
Note that this object is usually constructed via a derived classes, e.g. PredictionClassif or PredictionRegr.
as.data.table(rr)
Prediction -> data.table::data.table()
Converts the data to a data.table::data.table().
c(..., keep_duplicates = TRUE)
(Prediction, Prediction, ...) -> Prediction
Combines multiple Predictions to a single Prediction.
If keep_duplicates is FALSE and there are duplicated row ids,
the data of the former passed objects get overwritten by the data of the later passed objects.
data(named list())
Internal data structure.
task_type(character(1))
Required type of the Task.
task_properties(character())
Required properties of the Task.
predict_types(character())
Set of predict types this object stores.
man(character(1))
String in the format [pkg]::[topic] pointing to a manual page for this object.
Defaults to NA, but can be set by child classes.
row_ids(integer())
Vector of row ids for which predictions are stored.
truth(any)
True (observed) outcome.
missing(integer())
Returns row_ids for which the predictions are missing or incomplete.
format()
Helper for print outputs.
Prediction$format()
print()
Printer.
Prediction$print(...)
...(ignored).
help()
Opens the corresponding help page referenced by field $man.
Prediction$help()
score()
Prediction$score( measures = NULL, task = NULL, learner = NULL, train_set = NULL )
clone()
The objects of this class are cloneable with this method.
Prediction$clone(deep = FALSE)
deepWhether to make a deep clone.
Other Prediction:
PredictionClassif,
PredictionRegr
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