LTSA-LE: A Local Tangent Space Alignment Label Enhancement Algorithm |
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Authors: | Chao Tan Genlin Ji Richen Liu Yanqiu Cao |
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Affiliation: | School of Computer Science and Engineering,Southeast University,Nanjing 210096,and also with the School of Computer Science and Technology,Nanjing Normal University,Nanjing 210023,China;School of Computer Science and Technology,Nanjing Normal University,Nanjing 210023,China. |
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Abstract: | According to smoothness assumption, local topological structure can be shared between feature and label manifolds. This study proposes a new algorithm based on Local Tangent Space Alignment(LTSA) to implement the label enhancement process. In general, we first establish a learning model for feature extraction in label space and use a feature extraction method of LTSA to guide the reconstruction of label manifolds. Then, we establish an unconstrained optimization model based on the optimal theory presented in this paper. The model is suitable for solving problems with a large number of sample points. Finally, the experiment results show that the algorithm can effectively improve the training speed and multilabel dataset prediction accuracy. |
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