Dimensionality Reduction

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4 Terms

1
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What’s the difference between feature selection and extraction?

Selection: keep existing features; Extraction: create new features (e.g. PCA, LDA).

2
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What does explained_variance_ratio_ = [0.6, 0.3, 0.05] mean in PCA?

The 3 components explain 60%, 30%, and 5% of total variance → first component dominates.

3
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What does LDA do?

Finds projection maximizing class separation (between-class variance / within-class variance).

4
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What does PCA do?

Finds directions maximizing data variance (unsupervised).