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kml: K-Means for Longitudinal Data
An implementation of k-means specifically design to cluster longitudinal data. It provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical interface for choosing the 'best' number of clusters.
Getting started
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Package details |
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| Author | Christophe Genolini [cre, aut], Bruno Falissard [ctb], Patrice Kiener [ctb] |
| Maintainer | Christophe Genolini <christophe.genolini@u-paris10.fr> |
| License | GPL (>= 2) |
| Version | 2.4.6 |
| URL | http:www.r-project.org |
| Package repository | View on CRAN |
| Installation |
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