mldr (version 0.4.3)

remedial: Decouples highly imbalanced labels

Description

This function implements the REMEDIAL algorithm. It is a preprocessing algorithm for imbalanced multilabel datasets, whose aim is to decouple frequent and rare classes appearing in the same instance. For doing so, it aggregates new instances to the dataset and edit the labels present in them.

Usage

remedial(mld)

Arguments

mld

mldr object with the multilabel dataset to preprocess

Value

An mldr object containing the preprocessed multilabel dataset

See Also

concurrenceReport, labelInteractions

Examples

# NOT RUN {
library(mldr)
# }
# NOT RUN {
summary(birds)
summary(remedial(birds))
# }