In this article, we introduce the Stata implementation of a flow-based cluster algorithm, flowbca, written in Mata. The main purpose of flowbca is to identify clusters based on relational data of flows. We illustrate the command by providing multiple examples of applications from the research fields of economic geography, industrial input–output analysis, and social network analysis
Discovering interesting patterns or substructures in data streams is an important challenge in data...
<p>Cluster Flow is a pipelining tool to automate and standardise bioinformatics analyses on high-per...
Abstract—Clustering is used in many fields, including machine learning, data mining, financial mathe...
In this article, we introduce the Stata implementation of a flow-based cluster algorithm, flowbca, w...
In this article, we introduce the Stata implementation of a flow-based cluster algorithm written in ...
The paper presents research results referring to the use of flow networks and ant colony algorithm i...
Research on the problem of clustering tends to be fragmented across the pattern recognition, databas...
Submitted by Oliveira Flávia (flavia@sisbin.ufop.br) on 2015-04-13T20:16:40Z No. of bitstreams: 1 ...
Abstract—Traffic classification has become a crucial domain of research due to the rise in applicati...
This work is an overview of some of the most frequently used algorithms for cluster analysis and som...
Network analysis is a multidisciplinary research method that is quickly becoming a popular and excit...
Abstract. Packet header traces are widely used in network analysis. Header traces are the aggregate ...
Understanding the patterns and dynamics of spatial origin-destination flow data has been a long-stan...
Cluster Analysis for Applications deals with methods and various applications of cluster analysis. T...
In a number of problem domains there is an increasing interest in exploring flow data, which is defi...
Discovering interesting patterns or substructures in data streams is an important challenge in data...
<p>Cluster Flow is a pipelining tool to automate and standardise bioinformatics analyses on high-per...
Abstract—Clustering is used in many fields, including machine learning, data mining, financial mathe...
In this article, we introduce the Stata implementation of a flow-based cluster algorithm, flowbca, w...
In this article, we introduce the Stata implementation of a flow-based cluster algorithm written in ...
The paper presents research results referring to the use of flow networks and ant colony algorithm i...
Research on the problem of clustering tends to be fragmented across the pattern recognition, databas...
Submitted by Oliveira Flávia (flavia@sisbin.ufop.br) on 2015-04-13T20:16:40Z No. of bitstreams: 1 ...
Abstract—Traffic classification has become a crucial domain of research due to the rise in applicati...
This work is an overview of some of the most frequently used algorithms for cluster analysis and som...
Network analysis is a multidisciplinary research method that is quickly becoming a popular and excit...
Abstract. Packet header traces are widely used in network analysis. Header traces are the aggregate ...
Understanding the patterns and dynamics of spatial origin-destination flow data has been a long-stan...
Cluster Analysis for Applications deals with methods and various applications of cluster analysis. T...
In a number of problem domains there is an increasing interest in exploring flow data, which is defi...
Discovering interesting patterns or substructures in data streams is an important challenge in data...
<p>Cluster Flow is a pipelining tool to automate and standardise bioinformatics analyses on high-per...
Abstract—Clustering is used in many fields, including machine learning, data mining, financial mathe...