Clustering Algorithm for Travel Distance Analysis

Zenina Nadezda () and Borisov Arkady ()
Additional contact information
Borisov Arkady: Riga Technical University

Information Technology and Management Science, 2013, vol. 16, issue 1, 85-88

Abstract: An important problem in the application of cluster analysis is the decision regarding how many clusters should be derived from the data. The aim of the paper is to determine a number of clusters with a distinctive breaking point (elbow), calculating variance ratio criterion (VRC) by Calinski and Harabasz and J-index in order to check robustness of cluster solutions. Agglomerative hierarchical clustering was used to group a data set that is characterized by a complex structure, which makes it difficult to identify a structure of homogeneous groups. Stability of cluster solutions was performed by using different similarity measures and reordering cases in the dataset.

Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/itms-2013-0013 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:itmasc:v:16:y:2013:i:1:p:85-88:n:13

DOI: 10.2478/itms-2013-0013

Access Statistics for this article

Information Technology and Management Science is currently edited by J. Merkurjevs

More articles in Information Technology and Management Science from Sciendo
Bibliographic data for series maintained by Peter Golla ().