谁能向我解释StandardScaler?
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.
有人可以简单地向我解释一下吗?
Can anyone explain this to me in simple terms?
StandardScaler背后的想法是，它将转换您的数据，使其分布的平均值为0，标准差为1.
对于多变量数据，这是按功能进行的(换句话说，独立于数据的每一列).
在给定数据分布的情况下，数据集中的每个值都将减去平均值，然后除以整个数据集(或多变量情况下的特征)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).