【Scikit-Learn】信息熵、基尼不纯度图像

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

def entropy(px):
    return - (px * np.log2(px))

x = np.linspace(0.01, 1, 100)
plt.figure(figsize=(5, 3), dpi=200)
plt.title('$Entropy(x) = - P(x) * log_2(P(x))$')
plt.xlim(0, 1)
plt.ylim(0, 0.6)
plt.xlabel('P(x)')
plt.ylabel('Entropy')
plt.plot(x, entropy(x), 'r-');

def gini_impurity(px):
    return px * (1 - px)

x = np.linspace(0.01, 1, 100)
plt.figure(figsize=(5, 3), dpi=200)
plt.title('$Gini(x) = P(x) (1 - P(x))$')
plt.xlim(0, 1)
plt.ylim(0, 0.6)
plt.xlabel('P(x)')
plt.ylabel('Gini Impurity')
plt.plot(x, entropy(x), 'r-');