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 m...
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| Format: | Article |
| Language: | English |
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Vilnius University Press
2009-12-01
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| Series: | Lietuvos Matematikos Rinkinys |
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| Online Access: | https://www.journals.vu.lt/LMR/article/view/17982 |