A comparative study of two optimization clustering techniques on unemployment data

Barros, Elisa; Nunes, Alcina; Balsa, Carlos

http://hdl.handle.net/10198/10382

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
ProceedingsIO2013.pdf		648.03 KB	Adobe PDF	Download

Send Feedback

Authors

Barros, Elisa

Nunes, Alcina

Balsa, Carlos

Abstract(s)

An important strategy for data classi cation consists in organising data points in clusters. The k-means is a traditional optimisation method applied to cluster data points. Using a labour market database, we suggest the application of an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. This approach presents results consistent with the results obtained by the k-means.

Keywords

Clustering methods K-means Spectral clustering Unemployment data mining

URI

http://hdl.handle.net/10198/10382

Citation

Barros, Elisa; Nunes, Alcina; Balsa, Carlos (2013). A comparative study of two optimization clustering techniques on unemployment data. In XVI Congresso da Associação Portuguesa de Investigação Operacional. Bragança