It can be shown that, in functional data classification problems, perfect asymptotic classification is possible, making use of the intrinsic very high dimensional nature of functional data.This performance is often achieved by linear methods,which are optimal in important cases.These results point to a marked difference between classification for functional data and its counterpart in convemional multivariate analysis, where dimetion is kept fixed as sample size diverges.