Clustering via the Mean Shift Algorithm

Clustering of vector data and functional data using the mean shift algorithm (multi-core processing is supported) or its blurring version.


R package to perform clustering of vector data and functional data using the mean shift algorithm.

  • changes to the way "projectCurveWavelets" handles irregularly spaced data
  • minor fixes to Vignette 2
  • added support for functional data via wavelet smoothing and thresholding via the "projectCurveWavelets" function
  • included Vignette 1 - Clustering via the Mean Shift Algorithm
  • included Vignette 2 - Clustering Functional Data via the Mean Shift Algorithm
  • fixed a bug that caused the functions "msClustering" and "bmsClustering" to produce an error if called with a value different than the default value for the argument "kernel"
  • fixed a typo in the documentation of the function "msClustering": "options( mc.core=n.cores )" in the older documentation now correctly reads "options( mc.cores=n.cores )"
  • other minor edits to the package documentation

News

Reference manual

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install.packages("MeanShift")

1.1-1 by Mattia Ciollaro, a year ago


Browse source code at https://github.com/cran/MeanShift


Authors: Mattia Ciollaro and Daren Wang


Documentation:   PDF Manual  


GPL-3 license


Depends on parallel, wavethresh

Suggests knitr, rmarkdown


See at CRAN