Back to Topic 4.3 — Machine learning approaches
4.3.2Computer Science HL5 flashcards

Classification

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Card 1 of 54.3.2
4.3.2
Question

What does classification predict?

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All 5 Flashcards — Classification

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Card 1definition

Question

What does classification predict?

Answer

Which **category** something belongs to, learned from labelled examples — binary (two) or multi-class.

Card 2comparison

Question

Precision or recall — which is which?

Answer

**Precision**: of those flagged, how many really were? **Recall**: of the real cases, how many were caught?

Card 3concept

Question

Why is accuracy misleading on rare events?

Answer

A model answering "no" every time scores 99.9% on a 1-in-1,000 condition and finds **nothing**. Ask what a majority guesser would score.

Card 4concept

Question

What does lowering the decision threshold do?

Answer

Catches **more real cases** at the cost of **more false alarms** — recall rises, precision falls. It is a human judgement about which error is worse.

Card 5example

Question

Which error is worse: spam filter or cancer screening?

Answer

Opposite. Spam: a **false positive** (a real email lost) is worse. Screening: a **false negative** (a missed tumour) is worse.

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IB Computer Science Classification Flashcards | 4.3.2 | Aimnova