Affinity propagation python

from sklearn.cluster import AffinityPropagation
import numpy as np

X = np.array([[1, 2], [1, 4], [1, 0], [4, 2], [4, 4], [4, 0]])
clustering = AffinityPropagation(affinity = 'euclidean', random_state=5).fit(X)

labels = clustering.labels_ # label to each element
centers = clustering.cluster_centers_ # center of each cluster

# if you need a distance different from euclidean
# calculate your custom, pairwise distance among vectors 
# and store them into a matrix M. 
# Note: cluster_centers are no longer available

clustering = AffinityPropagation(affinity='precomputed', random_state=5).fit(M)

Source: scikit-learn.org

Similar codes

0 vote359 views1 answer
Extract year from astype('datetime64[ns]')
Python
14 votes414 views2 answers
Django static files / templates
Python
0 vote332 views1 answer
Import nifti to numpy
Python
0 vote348 views1 answer
Qubesos
Python
1 vote373 views1 answer
Get adjacent cells in grid
Python
6 votes360 views3 answers
Matplotlib subplots title
Python
17 votes357 views2 answers
Import "rest_framework.views" could not be resolved
Python
1 vote393 views2 answers
Django sum get 0 if none
Python
30 votes348 views2 answers
How do i limit decimals to only two decimals in python
Python
0 vote311 views1 answer
Python series get value
Python