Python中numpy函式的使用
阿新 • • 發佈:2019-01-23
一.求線性方程的斜率
①最小二乘法
import numpy as np
from numpy.linalg import inv #逆矩陣
from numpy import dot #矩陣乘
from numpy import mat #矩陣
#y=2x 求線性方程的斜率
X = mat([1, 2, 3]).reshape(3, 1) #reshape 的作用就是修改矩陣的維度
print(X)
Y = 2*X
# theta = (X'X)-1X'Y
theta = dot(dot(inv(dot(X.T, X)), X.T), Y)
print(theta)
②梯度下降演算法
import numpy as np from numpy.linalg import inv #逆矩陣 from numpy import dot #矩陣乘 from numpy import mat #矩陣 #y=2x 求線性方程的斜率 X = mat([1, 2, 3]).reshape(3, 1) #reshape 的作用就是修改矩陣的維度 Y = 2*X # theta = (X'X)-1X'Y #theta = dot(dot(inv(dot(X.T, X)), X.T), Y) #theta = theta - alpha*(theta*X-Y)*X 梯度下降演算法 theta = 1.0 alpha = 0.1 for i in range(100): theta = theta + np.sum(alpha * (Y - dot(X, theta))*X.reshape(1, 3))/3. print(theta)