An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification

  title={An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification},
  author={Zoulficar Younes and Fahed Abdallah and Thierry Denoeux},
In multi-label learning, each instance in the training set is associated with a set of labels, and the task is to output a label set for each unseen instance. This paper describes a new method for multi-label classification based on the Dempster-Shafer theory of belief functions to classify an unseen instance on the basis of its k nearest neighbors. The proposed method generalizes an existing single-label evidence-theoretic learning method to the multi-label case. In multi-label case, the frame… CONTINUE READING
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