MLeNN {mldr.resampling} | R Documentation |
Multilabel edited Nearest Neighbor (MLeNN)
Description
This function implements the MLeNN algorithm. It is a preprocessing algorithm for imbalanced multilabel datasets, whose aim is to identify instances with majoritary labels, and remove its neihgbors which are too different to them, in terms of active labels.
Usage
MLeNN(D, TH = 0.5, k = 3, neighbors = NULL, tableVDM = NULL)
Arguments
D |
mld |
TH |
threshold for the Hamming Distance in order to consider an instance different to another one. Defaults to 0.5. |
k |
number of nearest neighbours to check for each instance. Defaults to 3. |
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
Francisco Charte, Antonio J. Rivera, MarĂa J. del Jesus, and Francisco Herrera. MLeNN: A First Approach to Heuristic Multilabel Undersampling. Intelligent Data Engineering and Automated Learning – IDEAL 2014. ISBN 978-3-319-10840-7.