A few of them are able to deal with all three types of correlations simultaneously. To address this problem, in this article, we formulate multilabel feature selection as a local causal structure learning problem and propose a novel algorithm, M2LC. By learning the local causal structure of ...
As we know, Markov blanket (MB) is a key concept in Bayesian network, which can be used to represent the local causal structure of a variable and the selected optimal features for multi-label feature selection. To select casual features for multi-label learning, in this paper, Parents and ...
Feature selectionLabel matrix decompositionNoisy labelsIn practice, each instance may be labeled with a candidate label set that contains all relevant labels and some noisy labels, which is known as the partial multi-label learning problem. Since it is difficult for existing multi-label feature ...