Compared with the classical Support Vector Machines, the Least Squares Support Vector Machines lose the sparseness, which would influence the efficiency of re-learning.

• 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。