谁能给我解释一下 StandardScaler? [英] Can anyone explain me StandardScaler?

问题描述

我无法理解 sklearn文档中StandardScaler的页面.

I am unable to understand the page of the StandardScaler in the documentation of sklearn.

谁能用简单的术语向我解释一下?

Can anyone explain this to me in simple terms?

推荐答案

StandardScaler 背后的想法是，它将转换您的数据，使其分布具有平均值 0 和标准偏差 1.
在多元数据的情况下，这是按特征完成的(换句话说，对于每一列数据都是独立的).
给定数据的分布，数据集中的每个值都会减去平均值，然后除以整个数据集(或多元情况下的特征)的标准差.

The idea behind StandardScaler is that it will transform your data such that its distribution will have a mean value 0 and standard deviation of 1.
In case of multivariate data, this is done feature-wise (in other words independently for each column of the data).
Given the distribution of the data, each value in the dataset will have the mean value subtracted, and then divided by the standard deviation of the whole dataset (or feature in the multivariate case).

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