Before applying PCA to a dataset containing features with very different scales (e.g., age 0-100 and income 0-500000), what preprocessing step is essential?

Question

Answer

Apply log transformation to all features to make them normally distributed.

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Remove all features with low variance since they contribute nothing to PCA.

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No preprocessing is needed because PCA is scale-invariant by design.

Answer

Standardize (z-score normalize) each feature to zero mean and unit variance so no single feature dominates the principal components due to its scale.

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Before applying PCA to a dataset containing features with very different scales ...

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