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All 5 Flashcards — Feature selection
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Question
What is a feature?
Answer
One **input column** the model is given. Feature selection decides which ones it sees.
Question
What is data leakage?
Answer
A feature containing the answer, or one **not available at prediction time**. Test accuracy looks superb and then collapses in production.
Question
Why is an identifier a bad feature?
Answer
It is unique per row, so the model **memorises** rather than learns — perfect on training data, useless on anything new.
Question
Name four kinds of feature worth dropping.
Answer
**Irrelevant** (no relationship), **redundant** (duplicates another), **constant** (no information), **identifier** (memorises) — and above all **leaking**.
Question
Does dropping a sensitive attribute stop discrimination?
Answer
No. Other features **proxy** for it — postcode, school, employment history — and the model finds those instead.
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Topic 4.2 hub
Data preprocessing
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