梯度下降法1

python 梯度下降法

import numpy as np
import matplotlib.pyplot as plt
plot_x = np.linspace(-1, 6, 141)
plot_y = (plot_x - 2.5)**2 - 1
def dJ(theta):
    return 2 * (theta - 2.5)
def J(theta):
    return (theta - 2.5)**2 - 1
eta = 0.1
epsilon = 1e-8
theta = 0
theta_history = [theta]
while True:
    gradient = dJ(theta)
    last_theta = theta
    theta = theta - eta * gradient
    theta_history.append(theta)
    if (abs(J(theta) - J(last_theta))) < epsilon:
        break
plt.plot(plot_x, plot_y)
plt.plot(np.array(theta_history),
         J(np.array(theta_history)),
         color='r',
         marker='+')
plt.show()