Ckmeans.1d.dp (4.0.1)

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Optimal and Fast Univariate Clustering.

http://cran.r-project.org/web/packages/Ckmeans.1d.dp

A fast dynamic programming algorithm for optimal univariate clustering. Minimizing the sum of squares of within-cluster distances, the algorithm guarantees optimality and reproducibility. Its advantage over heuristic clustering algorithms in efficiency and accuracy is increasingly pronounced as the number of clusters k increases. With optional weights, the algorithm can also optimally segment time series and perform peak calling. An auxiliary function generates histograms that are adaptive to patterns in data. This package provides a powerful alternative to heuristic methods for univariate data analysis.

Maintainer: Joe Song
Author(s): Joe Song [aut, cre], Haizhou Wang [aut]

License: LGPL (>= 3)

Uses: testthat, knitr, rmarkdown
Reverse suggests: FunChisq, gsrc, xgboost

Released 2 months ago.


24 previous versions

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