Projection Based Clustering

A clustering approach applicable to every projection method is proposed here [Thrun/Ultsch,2017] . The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on the book "Projection-Based Clustering through Self-Organization and Swarm Intelligence" . Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ProjectionBasedClustering")

1.0.7 by Michael Thrun, 3 months ago


http://www.deepbionics.org


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


Authors: Michael Thrun [aut, cre, cph], Florian Lerch [aut], Felix Pape [aut], Kristian Nybo [cph], Jarkko Venna [cph]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, ggplot2, stats, graphics, vegan, deldir, geometry, GeneralizedUmatrix, shiny, shinyjs

Suggests DataVisualizations, fastICA, tsne, FastKNN, MASS, pcaPP, spdep, methods, pracma, grid, mgcv, fields, png, reshape2

Linking to Rcpp

System requirements: C++11


Suggested by DatabionicSwarm, GeneralizedUmatrix.


See at CRAN