MLSMOTE {mldr.resampling}

Synthetic oversampling of multilabel instances (MLSMOTE)

Description

This function implements the MLSMOTE algorithm. It is a preprocessing algorithm for imbalanced multilabel datasets, whose aim is to identify instances with minoritary labels, and generate synthetic instances based on their neighbor instances.

Usage

MLSMOTE(D, k, strategy = "ranking", tableVDM = NULL)

Arguments

D

mld mldr object with the multilabel dataset to preprocess

k

Number of neighbors to be considered when creating a synthetic instance

strategy

Strategy for choosing the synthetic labels. Possible values: "union", "intersection" and "ranking" (default)

tableVDM

Dataframe object containing previous calculations for faster processing. If it is empty, the algorithm will be slower

Value

A mld object containing the preprocessed multilabel dataset

Source

Charte, F., Rivera, A. J., del Jesus, M. J., & Herrera, F. (2015). MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation. Knowledge-Based Systems, 89, 385-397.