Calibrated Multi-label Classification with Label Correlations
Sign Up to like & getrecommendations! Published in 2018 at "Neural Processing Letters"
DOI: 10.1007/s11063-018-9925-2
Abstract: Multi-label classification is a special learning task where each instance may be associated with multiple labels simultaneously. There are two main challenges: (a) discovering and exploiting the label correlations automatically, and (b) separating the relevant… read more here.
Keywords: label; classification label; multi label; label correlations ... See more keywords
Local positive and negative correlation-based k-labelsets for multi-label classification
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.08.035
Abstract: Abstract Multi-label classification has attracted great attention from different domains. RAkEL (Random k-label sets) is an effective high-order multi-label learning approach. However, this method exploits label correlations randomly, which cannot make full use of label… read more here.
Keywords: classification; positive negative; multi label; label correlations ... See more keywords