Efficient algorithm for testing goodness-of-fit for classification of high dimensional data

Efficient algorithm for testing goodness-of-fit for classification of high dimensional data

Let us have a sample satisfying d-dimensional Gaussian mixture model (d is supposed to be large). The problem of classification of the sample is considered. Because of large dimension it is natural to project the sample to k-dimensional (k = 1,  2, . . .) linear subspaces using projection pursuit me...

Full description

Bibliographic Details
Main Author: Gintautas Jakimauskas
Format: Article
Language:English
Published: Vilnius University Press 2009-12-01
Series:Lietuvos Matematikos Rinkinys
Subjects:
Gausian mixture model
goodness-of-fit
Online Access:https://www.journals.vu.lt/LMR/article/view/17982

Similar Items

Similar Items