它们与标准正交笛卡尔向量相关。

They are related to the orthonormal Cartesian vectors.

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我们现在已经完整地构建了搜索向量空间，这种搜索将返回包含匹配查询的相关 LDAP 数据记录的文件名。

We now have a fully built vector space for searching that will return filenames containing the relevant LDAP data record where the query matches.

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一个支持向量机的支持向量数相关的VC维是怎样的？有一个公式，关于这两个量？

How is the VC dimension of a support-vector machine related to its number of support vectors? Is there a formula relating these two quantities?

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