Python中StandardScaler
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
x = sc.fit_transform(x)

一: 数组x标准化公式

为数组，为数组x的平均值，为数组x的标准差，则标准化的公式为：

import numpy as np
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
x = np.arange(1,6)       # x = np.array([1 2 3 4 5])
x_mean = np.mean(x)      # x_mean即为数组x的平均值
x_std = np.std(x)        # 数组x的标准差
print(x)
print(x_mean)            # 3
print(x_std)             # 1.4142135623730951
print((x-x_mean)/x_std)
#
[[-1.41421356]
 [-0.70710678]
 [ 0.        ]
 [ 0.70710678]
 [ 1.41421356]]
x = x.reshape(-1,1)      #需要将x转成列向量，否则会报错
print(sc.fit_transform(x))

## sc.fit_transform(x)
[[-1.41421356]
 [-0.70710678]
 [ 0.        ]
 [ 0.70710678]
 [ 1.41421356]]