Abstract An improved multi-label Gaussian random field algorithm is proposed to reduce the uncertainty of temporary labels. The spearman correlation matrix is used to build a label-relevant module instead of temporary labels. The results of comparative experiments show that the proposed algorithm is stable for temporary labels with tolerance and disturbance and it increases the accuracy of classification.
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2010, Vol. 23 
