Clustering with k-means: Programming Exercise

The two colabs demonstrate the concepts taught in the course. You've already completed parts of the second and third colabs earlier in the course.

Clustering Using Manual Similarity

Earlier in the course, you designed the manual similarity measure in the first three sections of this colab. Now you'll finish the clustering workflow in sections 4 & 5. Given that you customized the similarity measure for your dataset, you should see meaningful clusters.

You will:

  • Cluster using k-means with the manual similarity measure.
  • Generate quality metrics.
  • Interpret the result.
Colab
Clustering with a Manual Similarity Measure

Clustering Using Supervised Similarity

You saw the clustering result when using a manual similarity measure. Here, you'll compare the result to using a supervised similarity measure. You already designed the supervised similarity measure in the first three sections of this colab. Now you'll run sections 4 & 5.

You will:

  • Cluster using k-means with the supervised similarity measure.
  • Generate quality metrics.
  • Interpret the result.
Colab
Clustering with a Supervised Similarity Measure

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Clustering in Machine Learning