Discriminant analysis with a stochastic supervisor

摘要

We consider the problem of linear discriminant analysis for two p-variate normal distributions with a common covariance matrix, where the initial sample classification is done stochastically. Assuming a Beta model for this classification variable and its independence of the observed variable for each group, we derive the EM algorithm for maximum likelihood estimation of the parameters.