<｜begin▁of▁sentence｜>### Instruction:
As a gunsmith, you are familiar with the need for precision and accuracy in your work. Similarly, in the field of network analysis, ensuring accurate representation of data clusters is crucial. Imagine you are working on a project for a military client to analyze and visualize communication networks within a tactical unit. You have used the NetworkX library in Python to represent the relationships between individuals. Now, you are tasked with presenting the clusters detected within the network in a human-readable format. Could you provide guidance on using the `__str__` method from the Clustering class of NetworkX's community detection output to achieve this?
### Response:
from igraph import Graph

# Create a simple undirected graph
edges = [(0, 1), (1, 2), (2, 3), (3, 0), (0, 2)]
g = Graph(edges)

# Perform a community detection to get clustering
clustering = g.community_edge_betweenness()

# Convert the clustering to a human readable string
print(str(clustering))
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