How does PCA behave when applied before vs after train-test split?

Applying PCA before splitting can cause data leakage and inflate model performance.

PCA learns variance structure from entire dataset. If applied before train-test split, test data influences principal components, leading to information leakage. Proper approach is fitting PCA only on training data and transforming test data using the same model.