Back to Topic 4.3 — Machine learning approaches
4.3.4Computer Science HL5 flashcards

Clustering

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Card 1 of 54.3.4
4.3.4
Question

What does clustering do?

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All 5 Flashcards — Clustering

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Card 1definition

Question

What does clustering do?

Answer

Groups similar records with **no labels** — the groups are the output, which is what makes it unsupervised.

Card 2process

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.

Card 3concept

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.

Card 4concept

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.

Card 5concept

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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