Application of Principal Components Analysis Results in Visual Network Analysis

Andrey Sergeevich Denisenko¹ and Grigory Olegovich Krylov²

¹National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), 115409, Russia, Moscow, Kashirskoe highway, 31. ²Doctor of Physical and Mathematical Sciences, Financial University under the Government of the Russian Federation, 125993, Russia, Moscow, Leningradsky prospekt, 49.

ABSTRACT: The paper deals with the application of principal components analysis in a roleof a preprocessor of the source data and its role in visual network analysis process. Such kind of PCA application provides highlighting the most valuable objects in the source selection. By the example of analyzing financial data of companies of certain industry in order to measure their activity level authors show that principal components analysis could be used as a preprocessor for further analysis. As a result of the research, they show the integration and visualization of the integral scores in the process of visual network analysis and their role in simplifying the large data processing.

KEYWORDS: Principal component analysis; Visual network analysis; Financial flows

This work is licensed under a Creative Commons Attribution 4.0 International License.