Package: tglkmeans 0.5.7

Aviezer Lifshitz

tglkmeans: Efficient Implementation of K-Means++ Algorithm

Efficient implementation of K-Means++ algorithm. For more information see (1) "kmeans++ the advantages of the k-means++ algorithm" by David Arthur and Sergei Vassilvitskii (2007), Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, pp. 1027-1035, and (2) "The Effectiveness of Lloyd-Type Methods for the k-Means Problem" by Rafail Ostrovsky, Yuval Rabani, Leonard J. Schulman and Chaitanya Swamy <doi:10.1145/2395116.2395117>.

Authors:Aviezer Lifshitz [aut, cre], Amos Tanay [aut], Weizmann Institute of Science [cph]

tglkmeans_0.5.7.tar.gz

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Bug tracker:https://github.com/tanaylab/tglkmeans/issues

On CRAN:

algorithms-implementedkmeans

6 exports 7 stars 1.83 score 46 dependencies 16 scripts 499 downloads

Last updated 3 months agofrom:c4c3f74c36. Checks:OK: 1 NOTE: 5. Indexed: yes.

Exports:%>%downsample_matrixsimulate_dataTGL_kmeansTGL_kmeans_tidytglkmeans.set_parallel

Dependencies:clicodetoolscolorspacedigestdoFuturedplyrfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegtableisobanditeratorslabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmeparallellypillarpkgconfigplyrpurrrR6RColorBrewerRcppRcppParallelrlangscalestgstattibbletidyselectutf8vctrsviridisLitewithr