ignore warnings

import warnings warnings.filterwarnings('ignore')

import numpy as np from sklearn import preprocessing

X_train = np.array([[ 1., -1., 2.],[ 2., 0., 0.],[ 0., 1., -1.]])

创建最大最小归一化模型

min_max_scaler = preprocessing.MinMaxScaler()

对训练数据进行最大最小归一化

X_train_minmax = min_max_scaler.fit_transform(X_train) print(X_train_minmax)

X_test = np.array([[ -3., -1., 4.]]) #将相同的缩放应用到测试集数据中 X_test_minmax = min_max_scaler.transform(X_test) print(X_test_minmax)