A comparative study of two optimization clustering techniques on unemployment data

Barros, Elisa; Nunes, Alcina; Balsa, Carlos

http://hdl.handle.net/10198/10378

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Authors

Barros, Elisa

Nunes, Alcina

Balsa, Carlos

Abstract(s)

An important strategy for data classification 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/10198/10378

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. ISBN 979-972-745-153-1