<｜begin▁of▁sentence｜>### Instruction:
Given a dataset of multidimensional points, how can a divisive clustering algorithm that uses Gaussian mixture models for clustering be applied to recursively partition the data, and how are the final cluster labels assigned to each point in the dataset?
### Response:
from graspologic.cluster import DivisiveCluster
import numpy as np

# Simulate some data to cluster
np.random.seed(1)
X = np.random.randn(100, 2)

# Initialize the DivisiveCluster with GMM as the underlying clustering method
# and fit to the data X
cluster = DivisiveCluster(cluster_method='gmm', max_components=5)
cluster.fit(X)

# Predict cluster labels for X
labels = cluster.predict(X)

# Print the predicted cluster labels
print(labels)
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