================================================================
=							       =
=    Functions for Mean-Shift clustering of top-t rankings     =
=							       =
================================================================
Available at: www.stat.washington.edu/mmp/intransitive.html

First version of this package written by Le Bao (2008)
MS.m re-written by Marina Meila MMP@stat.washington.edu (2012) 

Citation: 

An Exponential Model for Infinite Rankings
Marina Meila, Le Bao; Journal of Machine Learning Research 11(Dec):3481−3518, 2010.

Please cite the work above if you use our code.

@Article{MBao:jmlr-infinite10,  
  author = 	 {Marina Meil\u{a} and Le Bao},
  title = 	 {An exponential family model over infinite rankings},
  journal = 	 {Journal of Machine Learning Research},
  year = 	 {2010}, 
  volume = 	 {10},
  pages = 	 {3481--3518},
  month = 	 {December},
  url = {http://jmlr.csail.mit.edu/papers/v11/meila10a/meila10a.pdf},
}

For more details see also:

@TechReport{BaoM:computing-exam-tr08,
  author = 	 {Le Bao and Marina Meil\u{a}},
  title = 	 {Clustering permutations by Exponential Blurring Mean-Shift},
  institution =  {University of Washington},
  year = 	 {2007},
  type = 	 {Department of Statistics},
  number = 	 {524},
  address = 	 {},
  month = 	 {},
  note = 	 {},
  annote = 	 {}
}

===============================================================

		Code overview

Type >help <function_name> at the Matlab prompt to see a detailed
			   description of each function

Scripts
-------
main.m			-- runs a clustering experiment comparing various
			   algorithms 
test_MS.m		-- compares the running times of MS.m and MS.0 (MMP)

Core functions
--------------
MS.m			-- mean-shift algorithm by MMP
MS0.m			-- original mean-shift code by Le Bao
MS_infinite.m		-- mean-shift algorithm for infinite permutations by
			   Le Bao

MBC_infinite.m		-- model-based (EM) clustering
K_means.m		-- K-means clustering 

Helper functions
----------------
clustering_error.m
compute_confusion.m
dKdiff.m	        -- Kendall distance, calls dK.m
dK.m			-- Kendall distance
make_Qp.m
sample_from_theta.m

--------------------------------------------------------------------
README for First version written by Le Bao (2008)

To run the code:

1. change working directory to the folder containing the codes
2. open main.m, choose model_option and simulation design

The core functions are MS_infinite() for mean-shit clustering, 
MBC_infinite() for model based clustering, and kmeans().