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.

Answer

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

Answer

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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