Prediction

Abstract Prediction Object

This is the abstract base class for task objects like PredictionClassif or PredictionRegr.

Prediction objects store the following information:

1. The row ids of the test set

2. The corresponding true (observed) response.

3. The corresponding predicted response.

4. Additional predictions based on the class and predict_type. E.g., the class probabilities for classification or the estimated standard error for regression.

Format

R6::R6Class object.

Construction

This object is constructed via a derived classes, e.g. PredictionClassif or PredictionRegr.

Fields

• row_ids :: (integer() | character()) Vector of row ids for which predictions are stored.

• truth :: any True (observed) outcome.

• task_type :: character(1) Stores the type of the Task.

• predict_types :: character() Vector of predict types this object stores.

• missing :: logical() Returns row_ids for which the predictions are missing or incomplete.

Methods

• 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 NULL for many measures, but some measures need to extract information from these objects.

S3 Methods

• 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.

See Also

Other Prediction: PredictionClassif, PredictionRegr

Aliases

• Prediction