Three-Cluster Scatter Plot
Figure 2.22 An artificial (X, Y) data set with three clusters generated via Gaussian blobs, illustrating how scatter plots reveal grouping structure in data.
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Figure 2.22 An artificial example of an (X, Y) data set that has three clusters.
Figure 2.22 — Three-cluster scatter plot
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs
X, truth = make_blobs(n_samples=600, centers=[[5, 7], [7, 3], [3, 3]], cluster_std=[0.6, 0.4, 0.8], random_state=2 )
# Colors: charcoal (top), teal (bottom-right), pink (bottom-left)
palette = ['dimgray', 'lightseagreen', 'palevioletred']
colors = [palette[t] for t in truth]
fig, ax = plt.subplots(figsize=(5, 5))
ax.scatter(X[:, 0], X[:, 1], s=50, c=colors, alpha=0.85)
ax.set_xlim(0, 10)
ax.set_ylim(0, 10)
ax.set_xlabel('X', fontsize=12)
ax.set_ylabel('Y', fontsize=12)
ax.set_xticks(range(0, 11, 2))
ax.set_yticks(range(0, 11, 2))
plt.tight_layout()
plt.savefig('three_clusters.png', dpi=150, bbox_inches='tight')
plt.show()