%基于熵的屬性離散化方法，參見《一種基于熵的連續屬性離散化方法》
function [result,dds]=shang(data)
[m,n]=size(data);
result=zeros(10,5);
for i=1:n
    %%%%%%%%%%%%%%%%%計算劃分點
    setpoints=[];
    seqs=[];
    locs=[];
    %%%%%%%%%%%%%%%當出現有相通屬性值的樣本點時，去掉其余的只保留一個，為后面
    %為后面計算斷點做準備
    [seqs,locs]=sort(data(:,i));
    se=seqs;
    for bbs=1:m-1
    if se(bbs)==se(bbs+1)
        qs=bbs+1;
        while se(bbs)==se(qs)
            se(qs)=inf;
        end
    end
    end
    se(find(se==inf))=[];
    newlen=length(se);
    %%%%%%%%%%%%%%%%%
    for j=1:newlen-1       %計算斷點的值
        setpoints(j)=(se(j)+se(j+1))/2;
    end
    %%%%%%%%%%%%%%%%%
    nn=length(setpoints);%計算現有內部斷點數
    for t1=1:nn+1   %計算各個斷點處的卡方統計值
   %%%%%%%%%%計算卡方分布值
    if t1==1
    s1=length(find(-inf<seqs&seqs<setpoints(t1)));%取區間內的全部屬性值對應的地址
    elseif t1==nn+1
    s1=length(find(setpoints(t1-1)<=seqs&seqs<inf));
    else
    s1=length(find(setpoints(t1-1)<=seqs&seqs<setpoints(t1)));
    end
    num(t1)=s1;
    P(t1)=s1/m;
    end%接 for t1=1:nn+1
    Hmin(1)=-sum(P.*log2(P));%初始熵值
    k0=length(setpoints);
    H0=Hmin(1);
    Ck=zeros(1,2);%初始化Ck,另Ck(2)=0是為了它能夠進入循環while Ck(2)-Ck(1)>=0
    %Ck(2)是合并區間后的值，在while循環中會設置
    %%%%%%%%%%%%%%%%%%循環
    symbol=0;
    while Ck(2)-Ck(1)>=0
    Ck(1)=Ck(2);
    if symbol==1
        setpt(ad)=[];
        setpoints=[];
        setpoints=setpt;
    end
    Q=[];
    H=[];
    num=[];
    setpt=[];
    nn=length(setpoints);%計算現有內部斷點數
    setpt=setpoints;
    for c1=1:nn%計算去掉每個斷點所得的熵值，找出其中熵差最小的一個作為合并對象
        setpoints=[];
        setpoints=setpt;
        setpoints(c1)=[];
        tt=length(setpoints);
        for t2=1:tt+1   %計算各個斷點處的卡方統計值
        %%%%%%%%%%計算卡方分布值
        if t2==1
        s1=length(find(-inf<seqs&seqs<setpoints(t2)));%取區間內的全部屬性值對應的地址
        elseif t2==tt+1
        s1=length(find(setpoints(t2-1)<=seqs&seqs<inf));
        else
        s1=length(find(setpoints(t2-1)<=seqs&seqs<setpoints(t2)));
        end
        num(t2)=s1;
        Q(t1)=s1/m;
        end%接 for t1=1:nn+1
        H(c1)=-sum(Q.*log2(Q));%后續計算所得熵值
    end
    symbol=1;
    [Hmin(2),ad]=min(H);
%     Ck(2)=(nn)*Hmin(2)-Hmin(1)*(nn-1);
    Ck(2)=(k0)*Hmin(2)-H0*(nn-1);
    
    Hmin(1)=Hmin(2);
    end
    nt=length(setpt);
    result(1:nt,i)=setpt;
end
pointsnum=[];
    %將各個區間的值離散化
    dds=zeros(m,n);
    for i=1:n
        locd=[];
        locd=result(:,i);
        locd(find(locd==0))=[];
        pointsnum(i)=length(locd)+1;%區間個數
        if length(locd)~=0
        for j=1:pointsnum(i)
            if j==1
                dds(find(-inf<data(:,i)&data(:,i)<=locd(j)),i)=j;
            elseif j==pointsnum(i)
                dds(find(locd(j-1)<=data(:,i)&data(:,i)<inf),i)=j;
            else 
                dds(find(locd(j-1)<=data(:,i)&data(:,i)<=locd(j)),i)=j;
            end
        end
        end
    end