Package: briKmeans 1.0

briKmeans: Package for Brik, Fabrik and Fdebrik Algorithms to Initialise Kmeans

Implementation of the BRIk, FABRIk and FDEBRIk algorithms to initialise k-means. These methods are intended for the clustering of multivariate and functional data, respectively. They make use of the Modified Band Depth and bootstrap to identify appropriate initial seeds for k-means, which are proven to be better options than many techniques in the literature. Torrente and Romo (2021) <doi:10.1007/s00357-020-09372-3> It makes use of the functions kma and kma.similarity, from the archived package fdakma, by Alice Parodi et al.

Authors:Javier Albert Smet <[email protected]> and Aurora Torrente <[email protected]>. Alice Parodi, Mirco Patriarca, Laura Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli, as contributors.

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briKmeans.pdf |briKmeans.html✨
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Last updated 2 years agofrom:cff507e4da. Checks:OK: 7. Indexed: yes.

Exports:brikelbowRulefabrikfdebrikkmakma.similarityplotKmeansClustering

Dependencies:bootclusterdepthToolsRcppRcppArmadillosplines2