FAQ: K-Means Clustering - Implementing K-Means: Step 4

This community-built FAQ covers the “Implementing K-Means: Step 4” exercise from the lesson “K-Means Clustering”.

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This exercise can be found in the following Codecademy content:

Data Science

Machine Learning

FAQs on the exercise Implementing K-Means: Step 4

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It’s weird to create variable k as the number of centroids, but then use range(3) sporadically.

Also be wary of the final implementation of the list comprehension for the points variable. The Hint fails to mention the need of typecasting to np.array. An alternative approach is

points = [(list(sepal_length_width[j]) for j in range(len(samples)) if labels[j] == i])