<｜begin▁of▁sentence｜>### Instruction:
As a dermatologist, I diagnose and treat diseases, disorders, and conditions of the skin, hair, and nails. Suppose you have a network of 50 individuals and you want to understand their relationships using the BANE model. You can represent this network using a fast_gnp_random_graph with 50 nodes and a probability for edge creation of 0.1. Additionally, if you have available random feature matrix data with shape (50, 4), you can use the BANE model to generate node embeddings based on this network and the feature matrix.
### Response:
import networkx as nx
from karateclub import BANE
import numpy as np

# Step 1: Create a random graph
G = nx.fast_gnp_random_graph(50, 0.1)

# Step 2: Create a random feature matrix
features = np.random.rand(50, 4)

# Step 3: Instantiate BANE model
model = BANE(dimensions=32, svd_iterations=20, seed=42, alpha=0.3, iterations=100, binarization_iterations=20)

# Step 4: Fit the BANE model
model.fit(G, features)

# Step 5: Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
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