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All 5 Flashcards — Clustering
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Question
What does clustering do?
Answer
Groups similar records with **no labels** — the groups are the output, which is what makes it unsupervised.
Question
What are the steps of k-means?
Answer
Choose k, place centres at random, **assign** each point to the nearest, **move** each centre to the mean of its members, repeat until stable.
Question
Why can k-means give different answers on the same data?
Answer
The starting centres are **random** and it finds a **local** optimum, so where it settles depends on where it began.
Question
Why must features be scaled before clustering?
Answer
k-means uses **distance**, so a feature measured in thousands dominates one measured in units — income would decide the clusters entirely.
Question
What does clustering NOT tell you?
Answer
What the clusters **mean**. It returns "cluster 0, 1, 2"; naming them is a human interpretation that nothing validates.
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Topic 4.3 hub
Machine learning approaches
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