| Attributes | Values |
|---|
| rdf:type
| |
| Description
| - The article deals with the cluster analysis of municipalities in the Liberec Region. It builds on the results of factor analysis, which defined seven significant factors that characterize the socio-economic status of communities. The input for cluster analysis was the factor loadings, which allowed making multi-dimensional classification of the studied municipalities. To build the structure of clusters there were used both hierarchical clustering methods and non-hierarchical clustering methods with the help of k-means. In the first case the Ward´s method was utilized to create clusters and the results were graphically displayed by tree diagram. With the help of the division procedure an initial cluster was divided into 2 to 4 smaller clusters. Two basic clusters can be classified as urban and rural. Urban cluster is characterized by better features of population, age structure, civic amenities and the branch structure. On the contrary, cluster consisting of rural communities has an aging population, population migrating to cities, poor civic amenities and the employment structure is dominated by manufacturing and agriculture. When lowering the clustering boundary, it can be found that rural cluster breaks down to agricultural, submountaneous and cross-border areas. In the second stage, the method of non-hierarchic clustering using k-means was applied on the results of factor analysis. A set of municipalities of the Liberec Region was gradually divided into 2 to 10 clusters, which were analyzed in detail using the R-square index and Calinski-Habarasz F index. Taking into account the requirement that the clusters were not formed only by a few elements and outlying values, the region was finally divided into 6 clusters, which can be classified as urban, micro-regional, economically weak and rural focused on housing, services and agriculture.
- The article deals with the cluster analysis of municipalities in the Liberec Region. It builds on the results of factor analysis, which defined seven significant factors that characterize the socio-economic status of communities. The input for cluster analysis was the factor loadings, which allowed making multi-dimensional classification of the studied municipalities. To build the structure of clusters there were used both hierarchical clustering methods and non-hierarchical clustering methods with the help of k-means. In the first case the Ward´s method was utilized to create clusters and the results were graphically displayed by tree diagram. With the help of the division procedure an initial cluster was divided into 2 to 4 smaller clusters. Two basic clusters can be classified as urban and rural. Urban cluster is characterized by better features of population, age structure, civic amenities and the branch structure. On the contrary, cluster consisting of rural communities has an aging population, population migrating to cities, poor civic amenities and the employment structure is dominated by manufacturing and agriculture. When lowering the clustering boundary, it can be found that rural cluster breaks down to agricultural, submountaneous and cross-border areas. In the second stage, the method of non-hierarchic clustering using k-means was applied on the results of factor analysis. A set of municipalities of the Liberec Region was gradually divided into 2 to 10 clusters, which were analyzed in detail using the R-square index and Calinski-Habarasz F index. Taking into account the requirement that the clusters were not formed only by a few elements and outlying values, the region was finally divided into 6 clusters, which can be classified as urban, micro-regional, economically weak and rural focused on housing, services and agriculture. (en)
|
| Title
| - Cluster Analysis of the Liberec Region Municipalities
- Cluster Analysis of the Liberec Region Municipalities (en)
|
| skos:prefLabel
| - Cluster Analysis of the Liberec Region Municipalities
- Cluster Analysis of the Liberec Region Municipalities (en)
|
| skos:notation
| - RIV/46747885:24310/12:#0001752!RIV13-TA0-24310___
|
| http://linked.open...avai/riv/aktivita
| |
| http://linked.open...avai/riv/aktivity
| |
| http://linked.open...vai/riv/dodaniDat
| |
| http://linked.open...aciTvurceVysledku
| |
| http://linked.open.../riv/druhVysledku
| |
| http://linked.open...iv/duvernostUdaju
| |
| http://linked.open...titaPredkladatele
| |
| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/46747885:24310/12:#0001752
|
| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - Calinski-Habarasz F index; F-ratio; recall coefficient; measure of disagreement; k-means clustering; Ward´s method; factor loadings; non-hierarchical cluster analysis; hierarchical cluster analysis; Cluster analysis (en)
|
| http://linked.open.../riv/klicoveSlovo
| |
| http://linked.open...ontrolniKodProRIV
| |
| http://linked.open...v/mistoKonaniAkce
| |
| http://linked.open...i/riv/mistoVydani
| |
| http://linked.open...i/riv/nazevZdroje
| - Proceedings of 30th International Conference Mathematical Methods in Economics 2012
|
| http://linked.open...in/vavai/riv/obor
| |
| http://linked.open...ichTvurcuVysledku
| |
| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...vavai/riv/projekt
| |
| http://linked.open...UplatneniVysledku
| |
| http://linked.open...iv/tvurceVysledku
| |
| http://linked.open...vavai/riv/typAkce
| |
| http://linked.open.../riv/zahajeniAkce
| |
| number of pages
| |
| http://purl.org/ne...btex#hasPublisher
| - Silesian University, School of Business Administration
|
| https://schema.org/isbn
| |
| http://localhost/t...ganizacniJednotka
| |
![[RDF Data]](/fct/images/sw-rdf-blue.png)
![[cxml]](/fct/images/cxml_doc.png)
![[csv]](/fct/images/csv_doc.png)
![[text]](/fct/images/ntriples_doc.png)
![[turtle]](/fct/images/n3turtle_doc.png)
![[ld+json]](/fct/images/jsonld_doc.png)
![[rdf+json]](/fct/images/json_doc.png)
![[rdf+xml]](/fct/images/xml_doc.png)
![[atom+xml]](/fct/images/atom_doc.png)
![[html]](/fct/images/html_doc.png)