Evaluation of projections, obtained by dimensionality reduction techniques
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 dimen...
Main Authors: | Kotryna Paulauskienė, Olga Kurasova |
---|---|
Format: | Article |
Language: | English |
Published: |
Vilnius University Press
2014-12-01
|
Series: | Lietuvos Matematikos Rinkinys |
Subjects: | |
Online Access: | https://www.journals.vu.lt/LMR/article/view/17697 |
Similar Items
-
Projection error evaluation for large multidimensional data sets
by: Kotryna Paulauskienė, et al.
Published: (2016-01-01) -
Quantitative and Qualitative Comparison of 2D and 3D Projection Techniques for High-Dimensional Data
by: Zonglin Tian, et al.
Published: (2021-06-01) -
Control point selection for dimensionality reduction by radial basis function
by: Kotryna Paulauskienė, et al.
Published: (2016-02-01) -
Dimensionality Reduction of Tensors Based on Local Homeomorphism and Global Subspace Projection Distance Minimum
by: Guokai Zhang, et al.
Published: (2020-01-01) -
Analyzing Quality Measurements for Dimensionality Reduction
by: Michael C. Thrun, et al.
Published: (2023-08-01)