How does PCA influence decision boundaries in classification models?

PCA can reshape decision boundaries by projecting data into a lower-dimensional space.

When PCA transforms features, classifiers operate in transformed space. This can simplify or distort decision boundaries depending on whether PCA preserves discriminative information. Linear models often benefit, while nonlinear separability may degrade.