Data Science, Statistics, Causality, Machine Learning, Analytics.
approaches the problem by deleting random Y’s for each observation (say, half). Classical PCA cannot handle missing values. Probabilistic PCA (PPCA), its Bayesian counterpart, handles missing values just fine. PCA models the y vector of each observation using y = Wx, where W is the weight matrix