Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context

Title
Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context
Authors
Keywords
Multi-label learning, ReliefF algorithm, Feature weighting, Feature selection, Multi-label classification, Label ranking
Journal
NEUROCOMPUTING
Volume 161, Issue -, Pages 168-182
Publisher
Elsevier BV
Online
2015-02-22
DOI
10.1016/j.neucom.2015.02.045

Ask authors/readers for more resources

Reprint

Contact the author

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now