Learning with categorical functional data
Cristian Preda
Université de Lille, Lille, France
Abstract:
Categorical functional data viewed as sample of continuous-time jump stochastic processes with finite set of state are considered in the framework of unsupervised and supervised statistical learning. Dimension reduction for visualisation, clustering and regression are illustrated through numerical simulation and application on health data.