Machine Learning, Dimensionality Reduction, Feature Selection, Curse Of Dimensionality, Feature Engineering.
class separability is maximised. Examples from same class are put closely together by the projection. Examples from different classes are placed far apart by the projection PCA orients data along the direction of the component with maximum variance whereas LDA projects the data to signify the class