ml34.py

import matplotlib.pyplot as plt
from matplotlib import style
style.use('ggplot')
import numpy as np
from sklearn.cluster import KMeans

X = np.array([[1,2],
              [1.5,1.8],
              [5,8],
              [8,8],
              [1,0.6],
              [9,11]])

# plt.scatter(X[:,0],X[:,1], s=150)
# plt.show()

clf = KMeans(n_clusters=2)
# clf = KMeans(n_clusters=6)
clf. fit(X)

centroids = clf.cluster_centers_
labels = clf.labels_

colors = 10 * ['g.', 'r.', 'c.', 'b.', 'k.']

for i in range(len(X)):
    plt.plot(X[i][0], X[i][1], colors[labels[i]], markersize=10)
plt.scatter(centroids[:, 0],centroids[:, 1], marker = "x", s=150, linewidths = 5, zorder = 10)
plt.show()