Projection pursuit is a method for nding interesting projections of high-dimensional multivariate data. Typically interesting projections are found by numerical maximizing some measure of non-normality of projected data (so-called projection index) over projection direction. The problem is to select the index for projection pursuit. In this article we compare performance of ve projection indices: projection indices based on ! 2, 2, Kolmogorov-Smirnov goodness-of- t mea- sures, entropy index and Friedman's index. It is supposed that ob- served random variable satis es a multidimensional Gaussian mixture modelVytauto Didžiojo universiteta
We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentro...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Projection pursuit is a multivariate statistical technique aimed at finding interesting data project...
Projection pursuit is searching for "interesting" (nonnormal) projections of multivariate data via o...
A standard method for analyzing high dimensional multivariate data is to view scatter-plots of 2-dim...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
Two projection indices are proposed for the construction of robust 2-sample linear discriminant func...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
A new projection-pursuit index is used to identify clusters and other structures in multivariate dat...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentro...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Projection pursuit is a multivariate statistical technique aimed at finding interesting data project...
Projection pursuit is searching for "interesting" (nonnormal) projections of multivariate data via o...
A standard method for analyzing high dimensional multivariate data is to view scatter-plots of 2-dim...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
Two projection indices are proposed for the construction of robust 2-sample linear discriminant func...
In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal ...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
A new projection-pursuit index is used to identify clusters and other structures in multivariate dat...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensio...
We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentro...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Projection pursuit is a multivariate statistical technique aimed at finding interesting data project...
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