Distributed Data Clustering by Neural Network Algorithms

被引：0

作者：

Kholod, Ivan I. ^{[1
]}

Rukavitsyn, Andrey N. ^{[1
]}

Reva, Nikita ^{[1
]}

Shorov, Andrey V. ^{[1
]}

机构：

[1] St Petersburg Electrotech Univ LETI, St Petersburg, Russia

来源：

PROCEEDINGS OF THE 2019 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (EICONRUS) | 2019年

关键词：

self-organizing maps; neural network; deep learning; clustering; data mining; distributed data; Big data;

D O I：

10.1109/eiconrus.2019.8657175

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The paper describes an analysis of the possibilities of applying Kohonen self-organizing maps for distributed data. We consider two strategies of distributed data analysis: with intermediate synchronization of results and with synchronization after full or partial construction of maps. Each strategy is considered taking into account both horizontal and vertical data distribution. We provide recommendations for the choice of a strategy depending on the type of data distribution. The obtained conclusions are confirmed by the results of an experiment.

引用

页码：249 / 253

页数：5

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