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Leer K-Means Model with 4 Clusters | Clustering Demystified
Clustering Demystified

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K-Means Model with 4 Clusters

Let's try to improve clustering results using the split on 4 separate clusters.

Taak

Swipe to start coding

  1. Evaluate the KMeans with 4 clusters.
  2. Fit the algorithm.

Oplossing

kmeans = KMeans(n_clusters=4, random_state=0)

kmeans.fit(X)

# check how many of the samples were correctly labeled
labels = kmeans.labels_

correct_labels = sum(y == labels)
print("Result: %d out of %d samples were correctly labeled." % (correct_labels, y.size))
print("Accuracy score: {0:0.2f}". format(correct_labels/float(y.size)))

Congratulations on completing the Clustering Project!

Mark tasks as Completed
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