classification - perception.py

#!/usr/bin/env python
# coding: utf-8

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import matplotlib.pyplot as plt
import numpy as np


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train = np.loadtxt(r'C:\Users\Gaodongyu\Documents\gaodongyu\10 math of ML\sourcecode-cn\sourcecode-cn\images1.csv', delimiter=',', skiprows=1)
train_x = train[:, 0:2]
train_y = train[:, 2]


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m


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w = np.random.rand(2)


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def f(x):
    if np.dot(w,x) >= 0:
        return 1
    else:
        return -1


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epoch = 10

count = 0
for _ in range(epoch):
    for x,y in zip(train_x, train_y):
        if f(x) != y:
            w = w + y * x
            count += 1
            print('第{}次: w = {}'.format(count, w))


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x1 = np.arange(0, 500)

plt.plot(train_x[train_y == 1, 0], train_x[train_y == 1, 1], 'o')
plt.plot(train_x[train_y == -1, 0], train_x[train_y == -1, 1], 'x')
plt.plot(x1, -w[0]/w[1] * x1, linestyle = 'dashed')
plt.show()


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print(f([200, 100]))
print(f([100, 200]))


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