p11.py

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use("ggplot")
from sklearn import svm

# x = [1, 5, 1.5, 8, 1, 9]
# y = [2, 8, 1.8, 8, 0.6, 11]
# plt.scatter(x,y)
# plt.show()

X = np.array(
  [
    [1,2],
    [5,8],
    [1.5,1.8],
    [8,8],
    [1,0.6],
    [9,11]
  ]
)
y = [0,1,0,1,0,1]
clf = svm.SVC(kernel='linear', C = 1.0)
clf.fit(X,y)
print(clf.predict([0.58,0.76]))
print(clf.predict([10.58,10.76]))
w = clf.coef_[0]
print(w)
a = -w[0] / w[1]
xx = np.linspace(0,12)
yy = a * xx - clf.intercept_[0] / w[1]
h0 = plt.plot(xx, yy, 'k-', label="non weighted div")
plt.scatter(X[:, 0], X[:, 1], c = y)
plt.legend()
plt.show()