Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance
A pair-wised constrained LGC is proposed to tackle with class distributions overlapping cases. A multiclass weighted LS-SVM algorithm is developed to regress any nonlinear vector-valued function. A new two-step learning framework is proposed to learning supervised model from labelled and unlabelled data.
posterior distribution learning supervised learning supervised manifold classification