MLSOL {mldr.resampling} | R Documentation |
Multi-label oversampling based on local label imbalance (MLSOL)
Description
This function implements the MLSOL algorithm. It is a preprocessing algorithm for imbalanced multilabel datasets, which applies oversampling on difficult regions of the instance space, in order to help classifiers distinguish labels.
Usage
MLSOL(D, P, k, neighbors = NULL, tableVDM = NULL)
Arguments
D |
mld |
P |
Percentage in which the original dataset is increased |
k |
Number of neighbors to be considered when computing the neighbors of an instance |
neighbors |
Structure with all instances and neighbors in the dataset. 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
A mld object containing the preprocessed multilabel dataset
Source
Liu, B., Blekas, K., & Tsoumakas, G. (2022). Multi-label sampling based on local label imbalance. Pattern Recognition, 122, 108294.