Sparse clustering of functional data

Davide Floriello and Valeria Vitelli

Journal of Multivariate Analysis, 2017, vol. 154, issue C, 1-18

Abstract: We consider the problem of clustering functional data while jointly selecting the most relevant features for classification. Functional sparse clustering is here analytically defined as a variational problem with a hard thresholding constraint ensuring the sparsity of the solution. First, a unique solution to sparse clustering with hard thresholding in finite dimensions is proved to exist. Then, the infinite-dimensional generalization is given and proved to have a unique solution under reasonable assumptions. Both the multivariate and the functional versions of sparse clustering with hard thresholding exhibit improvements on other standard and sparse clustering strategies on simulated data. A real functional data application is also shown.

Keywords: Sparse clustering; Functional data; Weighted distance; Variational problem (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.jmva.2016.10.008

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