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All 5 Flashcards — Classification
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Question
What does classification predict?
Answer
Which **category** something belongs to, learned from labelled examples — binary (two) or multi-class.
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?
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.
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.
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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Full study notes for Classification
Topic 4.3 hub
Machine learning approaches
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Computer Science exam skills
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