Abstract:Abstract:In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for each unseen instance. The widely known binary relevance method (BR) for multi-label classification considers each label as an independent binary problem. It is ignored in the literature due to inadequacy of not considering label correlations. In this paper, we present our double layer based classifier chains method (DCC), which overcomes disadvantages of BR and inherits… Show more
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