Answers for "k means clustering sklearn"

1

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_
Posted by: Guest on July-21-2021
0

scikit learn k means

from sklearn.cluster import KMeans
df = np.array([[1,4],[2,2],[2,5],[3,3],[3,4],[4,7],[5,6],[6,4],[6,7],[7,6],[7,9],[8,7],[8,9],[9,4],[9,8]])
kmeans = KMeans(n_clusters=3, init='k-means++', max_iter=300, n_init=10)
y_pred = kmeans.fit_predict(df)
Posted by: Guest on December-01-2020

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