CFSFDP.zip

function [Label,times,disN]=CFSFDPK(data,dc,k) t0=clock; [r,c]=size(data); dens=ones(1,r); Label=zeros(1,r); Cluster=zeros(1,r); disN=0; dmax=-1; for i=1:r %Neibor=[]; for j=i+1:r dis=0; for h=1:c dis=dis+(data(i,h)-data(j,h))^2; end dis=sqrt(dis); disN=disN+1; if dis<dc dens(i)=dens(i)+1; %Neibor(dens(i))=j; dens(j)=dens(j)+1; end if dmax==-1 || dmax<dis dmax=dis; end end end [Y,IY]=sort(dens,'descend'); %最大密度 Tag=IY(1); Cluster(Tag)=IY(Tag); Sep(Tag)=dmax; Res(Tag)=Sep(Tag)*dens(Tag); for i=2:r Ltm=IY(1:i-1); Tag=IY(i); dm=dmax; for j=1:i-1 dis=0; for h=1:c dis=dis+(data(Tag,h)-data(Ltm(j),h))^2; end dis=sqrt(dis); disN=disN+1; if dis<dm dm=dis; dl=Ltm(j); end end Sep(Tag)=dm; Res(Tag)=dm*dens(Tag); Cluster(Tag)=dl; end [X,IX]=sort(Res,'descend'); %centers=IX(1:k); for j=1:k Label(IX(j))=j; end for i=1:r if Label(IY(i))==0 W=Cluster(IY(i)); Label(IY(i))=Label(W); end end % l=1; % W=find(Label==0,1); % % while ~isempty(W) % Cur=W; % if Label(Cur)==0 % Label(Cur)=l; % if Cluster(Cur)~=Cur % W=Cluster(Cur); % else % W=find(Label==0,1); % l=l+1; % end % else % s=find(Label==l); % Label(s)=Label(Cur); % W=find(Label==0,1); % end % end times=etime(clock,t0); % new_class=Label; % [sums,cluster]=equation(new_class); % l=length(sums); % cs=unique(class); % n=length(cs)+2; % statistic=zeros(l,n); % statistic(:,1)=sums; % ms=0; % PE=0; % RE=0; % true_class=zeros(1,r); % for i=1:l % s=class_distribution(setdiff(cluster(i,:),0),cs,class); % for j=2:n-1 % statistic(i,j)=s(j-1); % end % [maxvalue,maxrow]=max(s); % attr_class=unique(class); % for clusteri=1:length(setdiff(cluster(i,:),0)) % if isequal(class(cluster(i,clusteri)),attr_class(maxrow)) % true_class(cluster(i,clusteri))=1; % end % end % statistic(i,n)=maxvalue/sums(i); % PE=PE+maxvalue/sums(i); % ms=ms+max(s); % end % for i=1:l % [maxvalue,maxrow]=max(statistic(i,[2:n-1])); % if sum(statistic(:,maxrow+1))~=0 % RE=RE+maxvalue/sum(statistic(:,maxrow+1)); % %RE=RE+max(statistic(:,i+1))/sum(statistic(:,i+1)); % end % end % AC=ms/r; % PE=PE/l; % RE=RE/l; % ARI=CorrectedRandIndex(Label,class); % NMI=MutualInfromation(Label,class); end