【机器学习基础】用Python画出几种常见机器学习二分类损失函数

import numpy as npimport mathimport matplotlib.pyplot as pltplt.rcParams['font.sans-serif'] = ['SimHei']plt.rcParams['axes.unicode_minus'] = Falseplt.figure(figsize=(10,8))x = np.linspace(start=-1, stop=2, num=1001, dtype=np.float)logi = np.log(1 + np.exp(-x)) / math.log(2)boost = np.exp(-x)y_01 = x < 0y_hinge = 1.0 - xy_hinge[y_hinge < 0] = 0
plt.plot(x, y_01, 'g-', mec='k', label='（0/1损失）0/1 Loss', lw=2)plt.plot(x, y_hinge, 'b-', mec='k', label='（合页损失）Hinge Loss', lw=2)plt.plot(x, boost, 'm--', mec='k', label='（指数损失）Adaboost Loss', lw=2)plt.plot(x, logi, 'r-', mec='k', label='（逻辑斯谛损失）Logistic Loss', lw=2)plt.grid(True, ls='--')plt.legend(loc='upper right',fontsize=15)plt.xlabel('函数间隔:$yf(x)$',fontsize=20)plt.title('损失函数',fontsize=20)plt.show()