Dimensionality reduction and classification using the distribution mapping exponent

: Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is something like effective dimensionality of multidimensional space. The method for classification of multivariate data is based on the 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 the DME-th power of these distances can be used as 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.

• Type: Conference
• Year: 2004
• Where: ESANN
• Authors: Marcel Jirina
• Keywords: Distribution Mapping, ESANN 2004, ESANN 2007, Multivariate Data, Multivariate Data Distribution