classify_gmm.m

patten regnization source从1-14章能运行

function classes = classify_GMM(X, mulist, sigmalist, weightlist);

% 单捞磐 笼钦 X俊辑 阿 氦磐俊 措茄 海捞令狼 盒幅甫 荐青 
% 捞 盒幅甫 烹窍咯 GMM葛胆捞 瘤沥窍绰 努贰胶 吝俊辑 窍唱肺 捞 氦磐甫 且寸
%
% 涝仿 牢磊:
% X: d*numpoints 单捞磐 青纺
% mulist : 阿 努贰胶俊 措茄 MUS甫 啊瘤绊 乐绰 府胶飘 
% sigmalist : 阿 努贰胶俊 措茄 SIGMAS甫 啊瘤绊 乐绰 府胶飘
% weightlist : 阿 努贰胶俊 措茄 WEIGHTS甫 啊瘤绊 乐绰 府胶飘 
% 
% 免仿 牢磊 :
% classes : 阿 单捞磐 痢俊 且寸等 努贰胶甫 啊瘤绊 乐绰 凯 氦磐 

  [d,numpoints] = size(X);
  
  %if (is_list(mulist) & is_list(sigmalist) & is_list(weightlist)) == 0
  %   error('classify_GMM(X, mulist, sigmalist, weightlist) : lists should be lists!');
  %end    
      
  numclasses = length(mulist);
  
  %if (length(weightlist) == length(sigmalist) & length(sigmalist) == numclasses)
  %   error('List lengths inconsistent!');
  %end    
  
  bestloglike = loglikeGMM(X,mulist{:,1},sigmalist{:,1},weightlist{:,1});
  classes = ones(1,numpoints);
  for c = 2:numclasses
    newloglike = loglikeGMM(X,mulist{:,c},sigmalist{:,c},weightlist{:,c});
    better_idx = find(newloglike > bestloglike);
    bestloglike(better_idx) = newloglike(better_idx);
    classes(better_idx) = c;
  end