Two-Dimension LDA
LDA, Linear Discriminant Analysis, is a classification method and a dimension reducion technique. I’ll focus more on classification. LDA calculates a linear discriminant function (which arises from assuming Gaussian distribution) for each class, and chooses a class that maximizes such function. The linear discriminant function therefore dictates a linear decision boundary for choosing a class. The decision boundary should be linear in the feature space. Discriminant analysis itself isn’t inherently linear.
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