python 实现对数据集的归一化的方法(0-1之间)

 #首先，引入两个库 ，numpy,sklearnfrom sklearn.preprocessing import MinMaxScalerimport numpy as np #将csv文件导入矩阵当中my_matrix = np.loadtxt(open("xxxx.csv"),delimiter=",",skiprows=0) #将数据集进行归一化处理scaler = MinMaxScaler( )scaler.fit(my_matrix)scaler.data_max_my_matrix_normorlize=scaler.transform(my_matrix) #最后的my_matrix_normorlize 实现了归一化my_matrix_normorlize

from sklearn.preprocessing import MinMaxScalerimport numpy as npmy_matrix = np.loadtxt(open("xxxx.csv"),delimiter=",",skiprows=0)scaler = MinMaxScaler( )scaler.fit(my_matrix)scaler.data_max_my_matrix_normorlize=scaler.transform(my_matrix)