Distribution Mapping Exponent for Multivariate Data Classification

Distribution-mapping exponent (DME) that is something like effective dimensionality of multidimensional space is introduced. The method for classification of multivariate data is based on local estimate of distribution mapping exponent for each point. Distances of all points of a given class of the training set from a given (unknown) point are searched and it is shown that the sum of reciprocals of DME-th power of these distances can be used as the probability density estimate. The classification quality was tested and compared with other methods using multivariate data from UCI Machine Learning Repository. The method has no tuning parameters.