<｜begin▁of▁sentence｜>### Instruction:
Given a karate club graph G with random node features, can you use the BANE model to get its node embeddings? The graph has an associated feature matrix with 5 random features per node. Use the BANE model with 32 embedding dimensions and the default settings for other hyperparameters like SVD iterations, alpha, and binarization iterations.
### Response:
import networkx as nx
from karateclub import BANE
import numpy as np

# Create a graph
G = nx.karate_club_graph()

# Create a feature matrix with random features
np.random.seed(42) # Ensure reproducible results
features = np.random.rand(G.number_of_nodes(), 5) # 5 features per node

# Initialize BANE model with specified dimensions and other hyperparameters
model = BANE(dimensions=32, svd_iterations=20, seed=42, alpha=0.3, iterations=100, binarization_iterations=20)

# Fit the model
model.fit(G, features)

# Get the resulting node embeddings
embeddings = model.get_embedding()

# Output the embeddings
print(embeddings)
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