1. A method for classification of a newly arrived multidimensional data point (MDP) in a dynamic data set, comprising the steps of: a) generating a well-conditioned basis in a source matrix of multidimensional data points; b) applying a single-scale out-of-sample extension (OOSE) to the newly arrived MDP on the well-conditioned basis to provide coordinates of an approximate location of the newly arrived MDP in an embedded space; and c) applying a multi-scale OOSE to the newly arrived MDP to provide improved coordinates of the newly arrived MDP location in the embedded space, thereby classifying the newly arrived MDP in relation to the source matrix multidimensional data points of the dynamic data set.