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Factor Analysis and PCA
Statistically reduce dimensionality
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My dataset contains [NUMBER] correlated variables that I want to reduce. Explain how to apply PCA: choosing the number of components (scree plot, explained variance), interpreting loadings, visualizing in the factorial plane, and biplot. Include Python code and how to use the components as features for [ML_TASK].
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Use Cases
Statistically reduce dimensionality
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