【LDA|ML】西瓜书习题3.4

from XiguaData import *
import numpy as np

x, d = load_data_3d0a()

# 已知西瓜数据3.0a前8个分类为0，其余分类为1
x0 = x[:8]
d0 = d[:8]
x1 = x[8:]
d1 = d[8:]
# LDA 线性判别分析
miu0 = np.mean(x0, axis=0)
miu1 = np.mean(x1, axis=0)
sigma0 = np.dot((x0 - miu0).transpose(), x0 - miu0)
sigma1 = np.dot((x1 - miu1).transpose(), x1 - miu1)
sigma = sigma0 + sigma1
u, s, v = np.linalg.svd(sigma)
for i in range(s.shape[0]):
    if np.abs(s[i]) > 0.0001:
        s[i] = 1.0 / s[i]
    else:
        s[i] = 0.0
s_inv = np.diag(s)
sigma_inv = np.dot(v.transpose(), np.dot(s_inv, u.transpose()))
w = np.dot(sigma_inv, miu0 - miu1)
# result: w = array([ 0.14650982,  0.73871557])

西瓜书习题3.4