Reference

The clusterpath package provides an R/C++ implementation of the algorithms described in Hocking et al. Proceedings of the 28th International Conference on Machine Learning (2011). If you use this software, please cite the conference paper: 

@InProceedings{Hocking-Clusterpath,
  author =    {Toby Hocking and Jean-Philippe Vert and Francis Bach and Armand Joulin},
  title =     {Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties },
  booktitle = {Proceedings of the 28th International Conference on Machine Learning (ICML-11)},
  series =    {ICML '11},
  year =      {2011},
  editor =    {Lise Getoor and Tobias Scheffer},
  location =  {Bellevue, Washington, USA},
  isbn =      {978-1-4503-0619-5},
  month =     {June},
  publisher = {ACM},
  address =   {New York, NY, USA},
  pages=      {745--752},
}

Examples

To use the code, first install and load the package and its dependencies in R.

install.packages(c("Rcpp","ggplot2","latticeExtra"))
install.packages("clusterpath",repos="http://r-forge.r-project.org")

You can also install clusterpath from source if you have Subversion:

system("svn checkout svn://scm.r-forge.r-project.org/svnroot/clusterpath/pkg/clusterpath clusterpath")
system("R CMD INSTALL clusterpath")

library(clusterpath)
## calculate the l1 clusterpath
breakpoints <- clusterpath.l1.id(iris[,1:4])
plot(breakpoints)
l1 clusterpath on the iris data 
## calculate the weighted l2 clusterpath
path <- clusterpath.l2(iris[,1:4],gamma=1)
plot(path,groups=iris$Species)
scatter plot matrix of the l2 clusterpath on the iris data 
## compare the 2 results.
## first find the multidimensional breakpoints:
bpts4d <- castbreakpoints(breakpoints)
## concatenate the solution path data.frames:
solutions <- rbind(bpts4d,path)
## plot the 2 paths using ggplot2:
ggplot(solutions,aes(Petal.Length,Petal.Width))+
  geom_path(aes(group=interaction(row,norm),colour=norm))
2d projection of l2 clusterpath on the iris data 
## From examples(cluster3d), requires package rgl.
## Compares l1 and l2 paths in 3 dimensions.
cluster3d(iris[,1:3],gamma=1)
3d clusterpath of iris data

Troubleshooting

There are two versions of clusterpath: one that depends on Rcpp and one that does not. Both contain the same functions for optimization and clustering. If one does not work, try installing the other:

install.packages("clusterpath",repos="http://r-forge.r-project.org")
library(clusterpath)
install.packages("clusterpathRcpp",repos="http://r-forge.r-project.org")
library(clusterpathRcpp)

Also, you may have to install a more recent version of R.

Other clusterpath solvers

Below is a list of all the clusterpath solvers that I know of. Please write me an email if I missed anything!

Author Language Norms Algorithm Code
Toby Dylan Hocking R/C/C++ 1, 2 Active set primal R packages clusterpath and clusterpathRcpp (R-Forge), source
Armand Joulin MATLAB Infinity Franck-Wolfe source zip
Eric C. Chi and Kenneth Lange R/C 2, Infinity AMA, ADMM R package cvxclustr (CRAN)
Gary K Chen, et al. C++ (GPU) 2 Proximal distance CONVEXCLUSTER
Daniel Duckworth Python 1, 2, Infinity Coordinate ascent cvxcluster

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