Numpy-Neuron / example /kmeans.py
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kmeans with example plot done and ready for deployment
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import json
import requests
import matplotlib.pyplot as plt
import seaborn as sns
ENDPOINT: str = "http://127.0.0.1:5000/"
request_params = {
"algorithm": "kmeans-clustering",
"arguments": {
"k": 3,
"max_iter": 100,
},
}
headers = {
"Content-Type": "application/json",
}
r = requests.post(
ENDPOINT,
headers=headers,
data=json.dumps(request_params),
)
def plot():
cluster_data = r.json()["clusters"]
# plot the clusters and data points
fig, ax = plt.subplots(figsize=(8, 6))
sns.set()
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="black"
)
ax.set_title("K-means Clustering")
ax.legend()
plt.show()
if __name__ == "__main__":
plot()