<｜begin▁of▁sentence｜>### Instruction:
As a choreographer preparing for a dance performance, you have a Newman-Watts-Strogatz small-world dance ensemble with 100 dancers, each linked to 3 nearest partners and with a 0.5 probability of switching partners, and their random attributes represented as a COO matrix of size 100 x 10. How would you utilize the FeatherNode model from the CIKM ‘20 paper to create individualized movement sequences for each dancer based on their attributes and connections within the ensemble?
### Response:
import networkx as nx
from karateclub import FeatherNode
import numpy as np
from scipy.sparse import coo_matrix

# Creating a synthetic graph
G = nx.newman_watts_strogatz_graph(100, 3, 0.5)

# Generating random node features
features = np.random.rand(100, 10)
features_coo = coo_matrix(features)

# Initializing FeatherNode with specified hyperparameters
model = FeatherNode(reduction_dimensions=64, svd_iterations=20, theta_max=2.5, eval_points=25, order=5, seed=42)

# Fitting the model
model.fit(G, features_coo)

# Getting the embeddings
embeddings = model.get_embedding()

print(embeddings)
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