a7

#program 7
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
# Data
x1 = np.array([3, 1, 1, 2, 1, 6, 6, 6, 5, 6, 7, 8, 9, 8, 9, 9, 8])
x2 = np.array([5, 4, 6, 6, 5, 8, 6, 7, 6, 7, 1, 2, 1, 2, 3, 2, 3])
# Plot original data
plt.scatter(x1, x2)
plt.xlim([0, 10])
plt.ylim([0, 10])
plt.title('Dataset')
plt.show()
# KMeans clustering
X = np.column_stack((x1, x2))
kmeans = KMeans(n_clusters=3).fit(X)
# Plot clustered data
for i, label in enumerate(kmeans.labels_):
 plt.plot(x1[i], x2[i], color=['b', 'g', 'r'][label], marker=['o',
'v', 's'][label], ls='None')
plt.xlim([0, 10])
plt.ylim([0, 10])
plt.show()