This work proposes an unsupervised classification algorithm for curves. It extends the density based multivariate cluster approach to the functional framework. In particular, the modes of the small-ball probability are used as starting points to build the clusters. A simulation study is proposed.
(2014). Clustering for functional data [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/31678
Clustering for functional data
2014-01-01
Abstract
This work proposes an unsupervised classification algorithm for curves. It extends the density based multivariate cluster approach to the functional framework. In particular, the modes of the small-ball probability are used as starting points to build the clusters. A simulation study is proposed.File allegato/i alla scheda:
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