最大值最小值归一化
1 # -*- coding: utf-8 -*- 2 """ 3 Created on Fri Sep 7 16:28:20 2018 4 5 @author: zhen 6 """ 7 # 最大值最小值归一化:(X-Xmin)/(Xmax-Xmin) 8 import numpy as np 9 import matplotlib.pyplot as plt 10 11 x = np.random.rand(100) 12 x = x.reshape(-1, 1) 13 14 rand = np.random.rand(100) * np.random.randint(10) 15 rand = rand.reshape(-1, 1) 16 # 获取Xmax,Xmin 17 x_max = np.max(rand) 18 x_min = np.min(rand) 19 20 result = [] 21 # 查找数组的索引:np.where(rand == i) 22 for i in rand: 23 result.append((float(i[0]) - x_min)/(x_max - x_min)) 24 25 result = np.array(result, dtype = float) 26 result = result.reshape(-1, 1) 27 # 可视化 28 plt.plot(x, rand, "r.", label="native") 29 plt.plot(x, result, "b.", linewidth=2, label="normalized") 30 31 plt.legend(loc="upper left") 32 plt.grid() 33 plt.show()
结果：
分析：可知，数据的离散性大大降低，数据之间的内聚性增加，数据更加密集！
