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Spectral methods for growth curve clustering (CROSBI ID 259244)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Majstorović, Snježana ; Sabo, Kristian ; Jung, Johannes ; Klarić, Matija Spectral methods for growth curve clustering // Central European journal of operations research, 26 (2018), 3; 715-737

Podaci o odgovornosti

Majstorović, Snježana ; Sabo, Kristian ; Jung, Johannes ; Klarić, Matija

engleski

Spectral methods for growth curve clustering

The growth curve clustering problem is analyzed and its connection with the spectral relaxation method is described. For a given set of growth curves and similarity function, a similarity matrix is defined, from which the corresponding similarity graph is constructed. It is shown that a nearly optimal growth curve partition can be obtained from the eigendecomposition of a specific matrix associated with a similarity graph. The results are illustrated and analyzed on the set of synthetically generated growth curves. One real- world problem is also given.

Curve clustering ; Similarity graph ; Laplacian matrix ; Modularity matrix ; Spectral methods

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Podaci o izdanju

26 (3)

2018.

715-737

objavljeno

1435-246X

1613-9178

Povezanost rada

Matematika

Indeksiranost