print('Top terms per cluster:')
order_centroids = model.cluster_centers_.argsort()[:, ::-1]
terms = vectorizer.get_feature_names()
for i in range(true_k):
    print('Cluster %d:' % i, end=' ')
for ind in order_centroids[(i), :10]:
    print(' %s' % terms[ind], end=' ')
print()
Кластеризация текстовых документов с использованием kmeans scikit-learn в Python