2 docs tagged with "feature-selection"

Reducing feature complexity while preserving information: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

Techniques for identifying and keeping only the most relevant features using filter, wrapper, and embedded methods.