Jolita Bernataviciene

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In this paper, the relative multidimensional scaling method is investigated. This method is designated to visualize large multidimensional data. The method encompasses application of multidimensional scaling (MDS) to the so-called basic vector set and further mapping of the remaining vectors from the analyzed data set. In the original algorithm of relative(More)
Visual data mining is an efficient way to involve human in search for a optimal decision. This paper focuses on the optimization of the visual presentation of multidimensional data. A variety of methods for projection of multidimensional data on the plane have been developed. At present, a tendency of their joint use is observed. In this paper, two(More)
Visualization harnesses the perceptual capabilities of humans to provide the visual insight into data. Structure preserving projection methods can be used for multidimensional data visualization. The goal of this paper is to suggest and examine the projection error minimization strategies that would allow getting a better and less distorted projection. The(More)
In this paper, the diagonal majorization algorithm (DMA) has been investigated. The research focuses on the possibilities to increase the efficiency of the algorithm by disclosing its properties. The diagonal majorization algorithm is oriented at the multidimensional data visualization. The experiments have proved that, when visualizing large data set with(More)
Glaucoma is one of the most insidious eye diseases the occurrence and progression of which a human does not feel. This article provides a brief overview of the eye nerve parameterization methods and algorithms. Parameterization itself is an important task that provides and uniquely defines the structure of the optic nerve disc and further can be used in(More)
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