Evaluation of projections, obtained by dimensionality reduction techniques
Articles
Kotryna Paulauskienė
Vilniaus universitetas
Olga Kurasova
Vilniaus universitetas
Published 2014-12-20
https://doi.org/10.15388/LMR.B.2014.26
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Keywords

projection quality evaluation
dimensionality reduction

How to Cite

Paulauskienė K. and Kurasova O. (2014) “Evaluation of projections, obtained by dimensionality reduction techniques”, Lietuvos matematikos rinkinys, 55(B), pp. 137–142. doi: 10.15388/LMR.B.2014.26.

Abstract

In this paper, the projection evaluation measures such as stress function, Spearman’s rho, Konig’s topology preservation, silhouette and Renyi entropy have been analyzed. The principal component analysis (PCA) and part–linear multidimensional projection (PLMP) techniques are used to reduce the dimensionality of the initial data set. The experiments have been carried out with seven real and artificial datasets. The experimental investigation has shown that several quality evaluation
measures have to be used when dimension reduction problem is solved.

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