from clusterzeug import (
birchcluster,
gaussianmixture,
opticscluster,
hdbscancluster,
dbscan,
agglomerativeclustering,
spectralclustering,
kmeanscluster,
minibatchkmeanscluster,
afinity_propagation,
mean_shift,
)
import numpy as np
import random
data = np.array(
[[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(100)],
dtype=np.int64,
)
a1 = birchcluster(data, n_clusters=10)
a2 = gaussianmixture(data, n_components=5)
a3 = opticscluster(data, min_samples=5)
a4 = hdbscancluster(data, min_cluster_size=5)
a5 = dbscan(data, eps=0.5, min_samples=5)
a6 = agglomerativeclustering(data, n_clusters=10)
a7 = spectralclustering(data, n_clusters=10)
res = kmeanscluster(data, n_clusters=10)
print(res)
res2 = minibatchkmeanscluster(data, n_clusters=10)
print(res2)
aff = afinity_propagation(data, damping=0.5, preference=-10)
print(aff)
ms = mean_shift(data,bandwidth=2.0)
print(ms)-
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Some functions for clustering
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hansalemaos/clusterzeug
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Some functions for clustering