Compared with the classical Support Vector Machines, the Least Squares Support Vector Machines lose the sparseness, which would influence the efficiency of re-learning.
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摘要最小二乘支持向量机相比传统的支持向量机,丧失了解的稀疏性,影响了二次学习的效率。
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