最大值最小值歸一化

# -*- coding: utf-8 -*-
"""
Created on Fri Sep  7 16:28:20 2018

@author: zhen
"""
# 最大值最小值歸一化:(X-Xmin)/(Xmax-Xmin)
import numpy as np
import matplotlib.pyplot as plt

x = np.random.rand(100)
x = x.reshape(-1, 1)

rand = np.random.rand(100) * np.random.randint(10)
rand = rand.reshape(-1, 1)
# 獲取Xmax,Xmin
x_max = np.max(rand)
x_min = np.min(rand)

result = []
# 查找數組的索引:np.where(rand == i)
for i in rand:
    result.append((float(i[0]) - x_min)/(x_max - x_min))
    
result = np.array(result, dtype = float)
result = result.reshape(-1, 1)
# 可視化
plt.plot(x, rand, "r.", label="native")
plt.plot(x, result, "b.", linewidth=2, label="normalized")

plt.legend(loc="upper left")
plt.grid()
plt.show()

結果：

分析：可知，數據的離散性大大降低，數據之間的內聚性增加，數據更加密集！