find_clusters.m

来自「clustering_code ,Clustering Through Rank」· M 代码 · 共 76 行

function [ind_clust,bgi] = Find_Clusters(dot_dist,mean_dist,num_c,preSet_Centers)

%
% Clustering Through Ranking On Manifolds
% Version 0.2
%
% Copyright by Markus Breitenbach and Gregory Z. Grudic
% This code is for your personal and research use only.
%
% http://www.cs.colorado.edu/~grudic/
% http://ucsu.colorado.edu/~breitenm/
%
% This software is provided "as is," without warranty of any kind, express
% or implied.  In no event shall the authors be held liable
% for any direct, indirect, incidental, special or consequential damages
% arising out of the use of or inability to use this software.
%

bgi=[];

if nargin<4
    preSet_Centers=[];
end;

if length(preSet_Centers) > 2
	pp=randperm(length(preSet_Centers)-1);
	pq=preSet_Centers(2:length(preSet_Centers));
	pq=pq(pp);
	preSet_Centers=[preSet_Centers(1), pq];
end;

if length(preSet_Centers)==0
    m_cls_pt = find(mean_dist == max(mean_dist));
else
    [m_cls_pt, preSet_Centers] = pop(preSet_Centers);
end;

if length(m_cls_pt)<1
    ind_clust=[];
    return;
end;
num_clusters = 1;
val_max(num_clusters,1) = mean_dist(m_cls_pt(1));
ind_clust(num_clusters,1) = m_cls_pt(1);

wt = 1-dot_dist(m_cls_pt(1),:);
next_mean = wt.*mean_dist;
%figure;plot(next_mean);

for num_clusters = 2:num_c
    if length(preSet_Centers)==0
        m_cls_pt = find(next_mean == max(next_mean));
    else
        [m_cls_pt, preSet_Centers] = pop(preSet_Centers);
    end;
    val_max(num_clusters,1) = mean_dist(m_cls_pt(1));
    ind_clust(num_clusters,1) = m_cls_pt(1);
    wt = (1-dot_dist(m_cls_pt(1),:)).*wt;
    next_mean = wt.*next_mean;
    %figure;plot(next_mean);
    t5 = 5;
end

%ind_clust = unique(ind_clust); % remove duplicates

return;

function [y,X]=pop(X)
if length(X)>0
    y=X(1);
    X=X(2:length(X));
else
    y=[];
end;
return;