题目内容

下面关于特征矩阵的归一化（Normalizer）的描述错误的是

A. 归一化是依照特征矩阵的行，即每个样本进行处理
B. 其目的是使样本向量在进行点乘运算或计算相似性时，拥有统一的标准，即都转化为“单位向量”，使每个样本的范式等于 1。
C. 归一化是主要是对特征矩阵中每个列，即同一特征维度的数值进行规范化处理
D. 常见的归一化公式为L1 范式和L2 范式

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A. [[0 0] [0 0] [1 1] [0 1]]
B. [[1 0] [1 0] [0 1] [1 1]]
C. [[0 0] [0 0] [0 0] [0 0]]
D. [[0 0] [0 0] [1 0] [1 0]]

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A. [0 1 1 1 0 0 1 1 1 1 0 1 1 0 0 1 2]
B. [0 0 1 0 1 0 0 0 0 0 1 0 0 1 1 0 0]
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D. 其它选项都不对

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A. #1
B. #2
C. #3
D. #4

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A. fit
B. fit_transform
C. transform
D. normalizer