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Learn Challenge: Implementing K-Means Clustering | K-Means
Cluster Analysis

bookChallenge: Implementing K-Means Clustering

Task

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You are given a synthetic dataset stored in the data variable.

  • Initialize a K-means model with 3 clusters, set random_state to 42, n_init to 'auto' and store it in the kmeans variable.
  • Fit the model on the dataset, predict the cluster labels, and store the result in the labels variable.
  • For each cluster i, extract the points belonging to this cluster and store the result in the cluster_points variable.

Solution

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SectionΒ 3. ChapterΒ 7
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bookChallenge: Implementing K-Means Clustering

Swipe to show menu

Task

Swipe to start coding

You are given a synthetic dataset stored in the data variable.

  • Initialize a K-means model with 3 clusters, set random_state to 42, n_init to 'auto' and store it in the kmeans variable.
  • Fit the model on the dataset, predict the cluster labels, and store the result in the labels variable.
  • For each cluster i, extract the points belonging to this cluster and store the result in the cluster_points variable.

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 3. ChapterΒ 7
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