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chyzh1986

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虫号: 1827378
注册: 2012-05-20
专业: 机构学与机器人

[求助] 有用过reliefF函数的吗？

有用过这个函数的吗：
function W = reliefF(Dnolabel,Dlabel,Num,k,typeD,Topn)
这里面的参数都代表什么，应该怎么设置呢？要是有个例子就更好了，谢谢~

函数内容如下：

function W = reliefF(Dnolabel,Dlabel,Num,k,typeD,Topn)
%
%    To achieve attribute ranking using reliefF
%    Dlabel is the array of the label for each record
%    The data in Dlabel should be format 1,2,3 and so on
%    Dnolabel is the array of each record without label
%    Num is loop time for randomly choose instance
%    k is the number of nearest hits and miss choosed
%    Weight is output and it is the ranking of each attribute
%    typeD is the type of Nolabel data, if it is numerical, typeD=0;
%    if it is nominal attributes, typeD=1;
%
[y,x]=size(Dnolabel);
W = zeros(1,Topn);
%calculate the label probability
LabelRange=max(Dlabel)-min(Dlabel)+1;
LabelCount=zeros(1,LabelRange);
LabelP=zeros(1,LabelRange);
for i=1:y
LabelCount(Dlabel(i))=LabelCount(Dlabel(i))+1;
end
for j=1:LabelRange
LabelP(j)=LabelCount(j)/y;
end
LabelP
%*********************************************
DistanceArray=zeros(y-1,2);
%Weight=zeros(1,x);
Weight=zeros(x,2);
Diff=0;
for i=1:x
dominoDiff(i) = max(Dnolabel(:,i))- min(Dnolabel(:,i));
end
%for each loop of random choose instance
for NumN=1:Num
NumN
%randomly choose a instance
InstanceId = round([y.*rand(1)]);
while InstanceId==0,
      InstanceId = round([y.*rand(1)]);
end
index = 1;
%calculate the distance to the choosed instance for each other instance
for i=1:y
      if (i~=InstanceId)
         for j=1:x
            DistanceArray(index,1)=DistanceArray(index,1)+...
                  (Dnolabel(i,j)-Dnolabel(InstanceId,j))^2;
         end
         DistanceArray(index,1)=(DistanceArray(index,1)/x)^(0.5);
         DistanceArray(index,2)=i;
         index = index+1;
      end
end
%sort distance ascending
DistanceArray=sortrows(DistanceArray,1);

Result=zeros(LabelRange,y);
classSize = zeros(1,LabelRange);
for i=1:y-1
      class = Dlabel(DistanceArray(i,2));
      classSize(class) = classSize(class)+1;
      Result(class,classSize(class))=DistanceArray(i,2);
end

%for each attribute
MissW=0; %the initial value for the part relative Miss in the weight
HitW=0; %the initial value for the part relative Hit in the weight
for AttributeNum=1:x
      %calculate the difference of min-max value in this attribute
      diff = Weight(AttributeNum,1);
      if (dominoDiff(AttributeNum)<0.0000001)
         Weight(AttributeNum,1)=0;
         Weight(AttributeNum,2)=AttributeNum;
         continue;
      end

      %calculate the weight for each attribute
  for i=1:k %k is the number of nearest neighbours chosen by user
idHit = Result(Dlabel(InstanceId),k );
         %for the Hits
         if(round(typeD)==0)
            diff = diff - abs( Dnolabel(idHit, AttributeNum) -...
                  Dnolabel(InstanceId, AttributeNum) )...
                  /dominoDiff(AttributeNum)/k;
         else
            if (round(Dnolabel(InstanceId,AttributeNum))...
                     ==round(Dnolabel(idHit, AttributeNum)))
                  diff=diff-0;
            else
                  diff=diff-1;
            end
         end
      end


      for c=1:LabelRange
         if (c==Dlabel(InstanceId))
            continue;
         end

         P=LabelP(c)/(1-LabelP(Dlabel(InstanceId)));
         for i=1:k
            idMiss = Result(c,i);
            %for the misses
            if (round(typeD)==0)
                  diff = diff + P*abs( Dnolabel(idMiss, AttributeNum) -...
                     Dnolabel(InstanceId, AttributeNum) )...
                     /dominoDiff(AttributeNum)/k;
            else
                  if (round(Dnolabel(InstanceId,AttributeNum))...
                        ==round(Dnolabel(idHit, AttributeNum)))
                     diff=diff;
                  else
                     diff=diff+1;
                  end
            end
         end
      end % for m=1:LabelRange
      Weight(AttributeNum,1)=diff;
      Weight(AttributeNum,2)=AttributeNum;
end %  for AttributeNum=1:x
end % for NumN=1:Num
Weight(AttributeNum,1)=diff/Num;
Weight(AttributeNum,2)=AttributeNum;
W1 = sortrows(Weight);
for i = 1:Topn
W(i) = W1(x-i+1,2);
end

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