Hands-On Machine Learning with C++

Linear discriminant analysis

Linear discriminant analysis (LDA) is a type of multivariate analysis that allows us to estimate differences between two or more groups of objects at the same time. The basis of discriminant analysis is the assumption that the descriptions of the objects of each k^th class are instances of a multidimensional random variable that's distributed according to the normal (Gaussian) law, , with an average, _, and the following covariance matrix:

The index, , indicates the dimension of the feature space. Consider a simplified ...