lda

Linear Discriminant Analysis (LDA)

Description: LDA reduces dimensions by maximizing class separability, transforming data to a space that best discriminates between classes.

Key Points:

• Maximizes class separability. Assumes normally distributed classes with identical covariances. Useful for supervised dimensionality reduction.

Applications: Pattern recognition, face recognition, bioinformatics.