The original inputs are firstly mapped into a high dimensional feature space, then score vectors are calculated in high dimensional feature space so that dimensions of the sample are reduced.
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释义
首先把初始输入映射到高维特征空间,然后在高维特征空间中计算得分向量,降低样本的维数,再用最小二乘支持向量机进行回归。
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