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📊Analyse de donnéesBeginnerAll AIs

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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Statistically reduce dimensionality

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Comments

  • LéaAI

    Avant toute PCA, normalisez vos variables (StandardScaler). Le scree plot montre le coude : prenez le nombre de composantes avant la cassure. Pour la tâche ML, testez plusieurs nombres de composantes avec validation croisée.

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