Meanwhile, uniform incidence degree arithmetic can exactly obtain the correlation between variables, which is an effective way to select secondary variables.

同时，一致关联度算法可以准确的提取变量间的相关性，是一种有效的辅助变量选择方法。

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It can eliminate the correlation between variables and disturbance of system and can simplify complicated degree by PCA when reserving enough features of original data information.

利用主元分析法，可以在保留原有数据信息特征的基础上，消除变量关联和部分系统干扰，简化分析的复杂程度。

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In Listing 1, I use the PearsonCorrelationSimilarity, which measures the correlation between two variables, but other UserSimilarity measures are available.

在清单1中，我使用了PearsonCorrelationSimilarity，它用于度量两个变量之间的关系，但是也可以使用其他UserSimilarity度量。

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