结果.txt

有关聚类的一些例子

>> proto = [
    0.6213    0.7373
    0.5226    0.8939
    0.9797    0.6614
    0.9568    0.0118
    0.8801    0.1991
    0.8757    0.0648 
    0.1730    0.2987
    0.2714    0.2844
    0.2523    0.4692
    ];
 protoClass = [
     1
     1
     1
     2
     2
     2 
     3
     3
     3
     ];
 data = [
    0.9883    0.4329
    0.5828    0.2259
    0.4235    0.5798
    0.5155    0.7604
    0.3340    0.5298 
    ];
>> 
>>  U=~isnan(proto); proto(~U)=0

proto =

    0.6213    0.7373
    0.5226    0.8939
    0.9797    0.6614
    0.9568    0.0118
    0.8801    0.1991
    0.8757    0.0648
    0.1730    0.2987
    0.2714    0.2844
    0.2523    0.4692

>> V=~isnan(data);data(~V)=0

data =

    0.9883    0.4329
    0.5828    0.2259
    0.4235    0.5798
    0.5155    0.7604
    0.3340    0.5298

>> d=abs(data.^2*U'+V*proto'.^2-2*data*proto')

d =

    0.2273    0.4294    0.0523    0.1783    0.0664    0.1482    0.6827    0.5360    0.5430
    0.2630    0.4498    0.3472    0.1857    0.0891    0.1117    0.1732    0.1004    0.1684
    0.0639    0.1085    0.3160    0.6070    0.3534    0.4697    0.1418    0.1104    0.0415
    0.0117    0.0179    0.2253    0.7551    0.4480    0.6136    0.3305    0.2862    0.1541
    0.1256    0.1681    0.4342    0.6562    0.4076    0.5097    0.0793    0.0641    0.0103

>> [sorted, proto_index] = sort(d')

sorted =

    0.0523    0.0891    0.0415    0.0117    0.0103
    0.0664    0.1004    0.0639    0.0179    0.0641
    0.1482    0.1117    0.1085    0.1541    0.0793
    0.1783    0.1684    0.1104    0.2253    0.1256
    0.2273    0.1732    0.1418    0.2862    0.1681
    0.4294    0.1857    0.3160    0.3305    0.4076
    0.5360    0.2630    0.3534    0.4480    0.4342
    0.5430    0.3472    0.4697    0.6136    0.5097
    0.6827    0.4498    0.6070    0.7551    0.6562


proto_index =

     3     5     9     1     9
     5     8     1     2     8
     6     6     2     9     7
     4     9     8     3     1
     1     7     7     8     2
     2     4     3     7     5
     8     1     5     5     3
     9     3     6     6     6
     7     2     4     4     4

>> proto_index = proto_index(1:3,:)

proto_index =

     3     5     9     1     9
     5     8     1     2     8
     6     6     2     9     7

>> knn_class = protoClass(proto_index)

knn_class =

     1     2     3     1     3
     2     3     1     1     3
     2     2     1     3     3

>> classLabel = unique(protoClass);
     nClass     = length(classLabel)

nClass =

     3

>> sum(knn_class == classLabel(1))

ans =

     1     0     2     2     0

>> classCounter(1, :) = sum(knn_class == classLabel(1))

classCounter =

     1     0     2     2     0

>> classCounter(2, :) = sum(knn_class == classLabel(2))

classCounter =

     1     0     2     2     0
     2     2     0     0     0

>> classCounter(3, :) = sum(knn_class == classLabel(3))

classCounter =

     1     0     2     2     0
     2     2     0     0     0
     0     1     1     1     3

>> [maxi, winner_label_index] =max(classCounter, [], 1)

maxi =

     2     2     2     2     3


winner_label_index =

     2     2     1     1     3

>> C = classLabel(winner_label_index)

C =

     2
     2
     1
     1
     3

>> A = data(C == classLabel(1), :)

A =

    0.4235    0.5798
    0.5155    0.7604

>>  A = data(C == classLabel(2), :)

A =

    0.9883    0.4329
    0.5828    0.2259

>>  A = data(C == classLabel(3), :)

A =

    0.3340    0.5298

>>