# Some functions for clustering
## Tested against Windows / Python 3.11 / Anaconda
## pip install clusterzeug
```python
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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"description": "\r\n# Some functions for clustering \r\n\r\n## Tested against Windows / Python 3.11 / Anaconda\r\n\r\n## pip install clusterzeug\r\n\r\n```python\r\n\r\n\r\nfrom clusterzeug import (\r\n birchcluster,\r\n gaussianmixture,\r\n opticscluster,\r\n hdbscancluster,\r\n dbscan,\r\n agglomerativeclustering,\r\n spectralclustering,\r\n kmeanscluster,\r\n minibatchkmeanscluster,\r\n afinity_propagation,\r\n mean_shift,\r\n)\r\nimport numpy as np\r\nimport random\r\ndata = np.array(\r\n [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(100)],\r\n dtype=np.int64,\r\n)\r\na1 = birchcluster(data, n_clusters=10)\r\na2 = gaussianmixture(data, n_components=5)\r\na3 = opticscluster(data, min_samples=5)\r\na4 = hdbscancluster(data, min_cluster_size=5)\r\na5 = dbscan(data, eps=0.5, min_samples=5)\r\na6 = agglomerativeclustering(data, n_clusters=10)\r\na7 = spectralclustering(data, n_clusters=10)\r\nres = kmeanscluster(data, n_clusters=10)\r\nprint(res)\r\nres2 = minibatchkmeanscluster(data, n_clusters=10)\r\nprint(res2)\r\naff = afinity_propagation(data, damping=0.5, preference=-10)\r\nprint(aff)\r\nms = mean_shift(data,bandwidth=2.0)\r\nprint(ms)\r\n\r\n```\r\n",
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