MLTL: Multilabel approach for the Tomek Link undersampling...

In mldr.resampling: Resampling Algorithms for Multi-Label Datasets

Multilabel approach for the Tomek Link undersampling algorithm (MLTL)

Description

This function implements the MLTL algorithm. It is a preprocessing algorithm for imbalanced multilabel datasets, whose aim is to identify tomek links (majoritary instances with a very different neighbor), and remove them. It's like MLeNN, with the number of neighbors being 1.

Usage

MLTL(D, TH, neighbors = NULL, tableVDM = NULL)

Arguments

D	mld mldr object with the multilabel dataset to preprocess
TH	threshold for the Hamming Distance in order to consider an instance different to another one.
neighbors	Structure with instances and neighbors. If it is empty, it will be calculated by the function
tableVDM	Dataframe object containing previous calculations for faster processing. If it is empty, the algorithm will be slower

Value

An mldr object containing the preprocessed multilabel dataset

Source

Pereira, R. M., Costa, Y. M., & Silla Jr, C. N. (2020). MLTL: A multi-label approach for the Tomek Link undersampling algorithm. Neurocomputing, 383, 95-105.

mldr.resampling documentation built on Aug. 22, 2023, 5:11 p.m.