zscore归一化：

minmax

from sklearn import preprocessing
from sklearn.preprocessing import StandardScaler
import numpy as np

# 数据
x = np.array([[1.,-1.,2.],
                [2.,0.,0.],
                [0.,1.,-1.]])
print('----------------minmaxscaler标准化-------------')
# 调用minmaxscaler标准化
min_max_scaler = preprocessing.MinMaxScaler()
x_minmax = min_max_scaler.fit_transform(x)
print(x_minmax)

# 手写minmaxscaler标准化
def MinMaxScaler(data):
    return (data-data.min(axis = 0))/(data.max(axis=0)-data.min(axis=0))
print(MinMaxScaler(x))

print('----------------zscore归一化-------------')
# 手写ZScoreScaler归一化
def ZScoreScaler(data):
    return (data-data.mean(axis = 0))/data.std(axis = 0)
print(ZScoreScaler(x))

# 调库
zscaler = StandardScaler () 
x_zscore = zscaler.fit_transform(x)
print(x_zscore)