Abstract:

Aiming at the co-occurrence and relevance among the multi-label data,a novel multi-label classification algorithm using adaptive linear regression is proposed. In the algorithm,first,the classical linear regression theory is extended to the multi-label linear regression. Then,the threshold for the regression results is set by combining various evaluation criteria,thus adaptively predicting the final labels. The proposed algorithm considers not only the fixed threshold corresponding to the averages but also the adaptive thresholds reflecting the comprehensive effects of the classifier,thus reducing the influence of the distribution and noise of original data on the classification. Experimental results demonstrate that the proposed algorithm is effective in the multi-label classification.

Key words: multi-label, classification algorithm, linear regression, adaptive threshold learning