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

0 vote268 views1 answer
Sentiment analysis french python
Python
4 votes326 views5 answers
Min max python
Python
17 votes389 views6 answers
Installing django
Python Django
0 vote260 views1 answer
Password protected cmd python
Python
0 vote278 views1 answer
In deserialize_keras_object raise ValueError('Unknown ' + printable_module_name + ':' + object_name) ValueError: Unknown loss function:contrastive_loss
Python
0 vote219 views1 answer
First rows of data frame (specify n by param)
Python
0 vote288 views1 answer
Change version of python that poetry use
Python
1 vote268 views1 answer
Enumerate string pythonm
Python
0 vote326 views2 answers
How to use django-filters with viewset
Python Django
0 vote295 views2 answers
Remove leading and lagging spaces dataframe python
Python