remedial: Decouples highly imbalanced labels

In mldr: Exploratory Data Analysis and Manipulation of Multi-Label Data Sets

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

Source

F. Charte, A. J. Rivera, M. J. del Jesus, F. Herrera. "Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels". Proc. 2015 International Conference on Hybrid Artificial Intelligent Systems (HAIS 2015), pp. 489-501, Bilbao, Spain, 2015

See Also

concurrenceReport, labelInteractions

Examples

library(mldr)
## Not run: 
summary(birds)
summary(remedial(birds))

## End(Not run)

mldr documentation built on Jan. 11, 2020, 9:18 a.m.