Economies Clustering Using SOM-Based Dissimilarity

被引：1

作者：

Chudziak, Adam ^{[1
]}

机构：

[1] Warsaw Sch Econ, Niepodleglosci 128, PL-02554 Warsaw, Poland

来源：

ENGINEERING APPLICATIONS OF NEURAL NETWORKS, EANN 2016 | 2016年 / 629卷

关键词：

Self-Organising Maps; Hierarchical clustering; Dissimilarity; Political economy; Country clusters;

D O I：

10.1007/978-3-319-44188-7_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Clustering of countries and economies has been done for a long time by expert comparing to ideal theoretical entities. More recently a data driven approach has been taken, including, so called, black box methods. In this paper a SOM-based dissimilarity measure is presented and used for agglomerative hierarchical clustering of economies. It turns out that the results differ significantly from those obtained via a more traditional Euclidean distance based approach.

引用

页码：111 / 122

页数：12

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