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无偏置v-支持向量回归优化问题研究

, PP. 866-870

Keywords: 偏置,v-,支持向量回归机,优化问题

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Abstract:

在高维特征空间中,具有支持向量机形式的学习机的决策超平面倾向于通过原点,并不需要偏置.但在v-支持向量回归机(v-SVR)中存在偏置,为了研究偏置在v-SVR中的作用,提出了无偏置的v-SVR优化问题并给出其求解方法.在标准数据集上的实验表明,无偏置v-SVR的泛化性能好于v-SVR.根据对偶优化问题的解空间分析,偏置b不应包含在v-SVR优化问题中,v-SVR的决策超平面在高维特征空间中应通过原点.

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