Binary Information Press
Multi label classification is one of the hotspots of data mining and machine learning. An instance may belong to a set of labels simultaneously, and the number of samples which represent by the same instance but with different corresponding labels is imbalanced. The existing evaluation algorithm can not reflect the real performance of one classifier. In order to evaluate the classifier's accuracy more reasonably, a weights-based accuracy evaluation method is proposed. By giving different weight to each sample's classifying result and it can evaluate the real performance of one classifier effectively.