opt_alpha_sigma.m

clustering_code ,Clustering Through Ranking On Manifolds Version 0.2 Copyright by Markus Breit

function [my_alpha_opt,my_sigma_opt,my_num_classes_opt] = Opt_Alpha_Sigma(dst,lrn_par,dim,n)

%
% 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.
%


for class_ind = 1:length(lrn_par.Cluster_Search)
    
    num_classes = lrn_par.Cluster_Search(class_ind);
    SIGMA_ONLY = 1;
    cost = [];
    
    my_sigma = lrn_par.OPT_SIGMA_MIN_INTERVEL:lrn_par.OPT_SIGMA_DEL_INTERVEL:lrn_par.OPT_SIGMA_MAX_INTERVEL;
    for i = 1:length(my_sigma)
        cost(i) = cost_alpha_sigma(my_sigma(i),dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
        indt = find(cost~=1000);
        if length(indt) > 2
            os_min = my_sigma(i);
            if cost(i-1) < cost(i-2) & cost(i-1) < cost(i) % find dip
                %plot(my_sigma(cost~=1000),cost(cost~=1000))
                
                options = optimset('Display','iter','MaxFunEvals',lrn_par.SIGMA_MaxFunEvals);
                
                
                %[x,fval] = fminbnd(@cost_alpha_sigma,my_sigma(i-2),my_sigma(i),options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);		
                [x,fval] = fminbnd('cost_alpha_sigma',my_sigma(i-2),my_sigma(i),options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
                
                break;
                
            elseif cost(i-1) < cost(i)
                
                %plot(my_sigma(cost~=1000),cost(cost~=1000))
                
                %options = optimset('Display','iter','TolFun',1e-8,'MaxIter',10);
                options = optimset('Display','iter','MaxIter',lrn_par.OPT_ITER_INIT_SIGMA);
                
                %[x,fval] = fminbnd(@cost_alpha_sigma,my_sigma(i-3),my_sigma(i),options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
                [x,fval] = fminbnd('cost_alpha_sigma',my_sigma(i-3),my_sigma(i),options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
                
                break;
                
            end
        end
        t5555 = 0;
    end
    
    % debug
    x_s = x;
    fval_s = fval;
    
    my_alpha = lrn_par.my_alpha;
    if my_alpha <= 0
        my_alpha = 0.99;
    end
    
    if lrn_par.OPT_S_A == 1 
        
        x_t = zeros(2,1);
        x_t(1,1) = x;
        x_t(2,1) = my_alpha;
        
        
        options = optimset('Display','iter','MaxFunEvals',lrn_par.SIGMA_ALPHA_MaxFunEvals,'LargeScale','off');
        
        lb = zeros(size(x_t));
        lb(1,1) = lrn_par.OPT_SIGMA_MIN_INTERVEL;
        lb(2,1) = 1e-8;
        ub = zeros(size(x_t));
        ub(1,1) = lrn_par.OPT_SIGMA_MAX_INTERVEL;
        ub(2,1) = 1-(1e-8);
        
        SIGMA_ONLY = 0;
        
        %[x,fval] = fmincon(@cost_alpha_sigma,x_t,[],[],[],[],lb,ub,[],options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
        [x,fval] = fmincon('cost_alpha_sigma',x_t,[],[],[],[],lb,ub,[],options,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
        
       
        tmp_my_alpha_opt(class_ind) = x(2);
        
    end
    
    opt_val(class_ind) = fval;
    tmp_o_sigma(class_ind)= sqrt(dim*x(1)^2);
 
    % debug
    [tst_x,tst_clus_close] = cost_alpha_sigma(x,dst,num_classes,n,SIGMA_ONLY,dim,lrn_par);
    
    t77 = 1;
end

ind_best = find(opt_val == min(opt_val));

if lrn_par.OPT_S_A == 1
    my_alpha_opt = tmp_my_alpha_opt(ind_best);
else
    my_alpha_opt = 0.99;
end

my_sigma_opt = tmp_o_sigma(ind_best);

my_num_classes_opt = lrn_par.Cluster_Search(ind_best);

t77 = 1;