Abstract Prediction Object
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.
character()) Vector of row ids for which predictions are stored.
anyTrue (observed) outcome.
character(1)Stores the type of the Task.
character()Vector of predict types this object stores.
row_idsfor which the predictions are missing or incomplete.
score(measures = NULL, task = NULL, learner = NULL)(
list()of Measure, Task, Learner) -> Prediction Calculates the performance for all provided measures If no measure is provided, defaults to the measure defined in mlr_reflections$default_measures (mlr_measures_classif.ce for classification and mlr_measures_regr.mse for regression). Task and Learner may be
NULLfor many measures, but some measures need to extract information from these objects.
c(..., keep_duplicates = TRUE)(Prediction, Prediction, ...) -> Prediction Combines multiple
Predictions to a single
FALSEand there are duplicated row ids, the data of the former passed objects get overwritten by the data of the later passed objects.