Set threshold of prediction object for classification or multilabel classification. Creates corresponding discrete class response for the newly set threshold. For binary classification: The positive class is predicted if the probability value exceeds the threshold. For multiclass: Probabilities are divided by corresponding thresholds and the class with maximum resulting value is selected. The result of both are equivalent if in the multi-threshold case the values are greater than 0 and sum to 1. For multilabel classification: A label is predicted (with entry TRUE) if a probability matrix entry exceeds the threshold of the corresponding label.

setThreshold(pred, threshold)

## Arguments

pred (Prediction) Prediction object. (numeric) Threshold to produce class labels. Has to be a named vector, where names correspond to class labels. Only for binary classification it can be a single numerical threshold for the positive class.

## Value

(Prediction) with changed threshold and corresponding response.

## Examples

# create task and train learner (LDA)
lrn = makeLearner("classif.lda", predict.type = "prob")
#> Error: Please use column names for x
#> Error in as.data.frame(pred): object 'pred' not found