Kmeans sklearn

from sklearn.cluster import KMeans
import numpy as np
X = np.array([[1, 2], [1, 4], [1, 0],
              [10, 2], [10, 4], [10, 0]])
kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
kmeans.labels_

kmeans.predict([[0, 0], [12, 3]])

kmeans.cluster_centers_

Source: scikit-learn.org

Similar codes

1 vote59 views1 answer
Leaky relu keras
Python
10 votes110 views3 answers
Replace nan with mean
Python
0 vote103 views1 answer
Celery timezone setting django
Python
0 vote93 views1 answer
Plt title color
Python
0 vote116 views1 answer
"Token" is not defined Pylance
Python
0 vote118 views1 answer
How to use python-socker.io with fast api
Python
0 vote108 views1 answer
Powershell get list of groups and members
Python
0 vote103 views1 answer
Flip a coin with array in python
Python
6 votes116 views4 answers
Gamestop
Python
1 vote101 views4 answers
Drop duplicate index pandas
Python