mlr (version 1.1-18)

setThreshold: Set threshold of prediction object.

Description

Set threshold of prediction object for 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.

Usage

setThreshold(pred, threshold)

Value

[Prediction] with changed threshold and corresponding response.

See Also

predict

Examples

## create task and train learner (LDA)
task <- makeClassifTask(data = iris, target = "Species")
lrn <- makeLearner("classif.lda", predict.type = "prob")
mod <- train(lrn, task)

## predict probabilities and compute performance
pred <- predict(mod, newdata = iris)
performance(pred, measure = mmce)
head(as.data.frame(pred))
## adjust threshold and predict probabilities again
threshold <- c(setosa = 0.4, versicolor = 0.3, virginica = 0.3)
pred <- setThreshold(pred, threshold = threshold)
performance(pred, measure = mmce)
head(as.data.frame(pred))