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import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import io
matplotlib.use("Agg")
sns.set()
def plot(clusterer, X):
cluster_data = clusterer.to_dict(X)["clusters"]
fig, ax = plt.subplots(figsize=(8, 6))
for cluster in cluster_data:
sns.scatterplot(
x=[point[0] for point in cluster["points"]],
y=[point[1] for point in cluster["points"]],
label=f"Cluster {cluster['cluster_id']}",
ax=ax,
)
ax.scatter(
x=cluster["centroid"][0],
y=cluster["centroid"][1],
marker="x",
s=100,
linewidth=2,
color="red",
)
ax.legend()
ax.set_title("K-means Clustering")
ax.set_ylabel("Normalized Petal Length (cm)")
ax.set_xlabel("Normalized Petal Length (cm)")
# Save the plot to a BytesIO buffer
buffer = io.BytesIO()
plt.savefig(buffer, format='png')
buffer.seek(0)
return buffer.read()
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