X-SOM finished!
Christoph Budziszewski commited on 2009-04-07 15:54:26
Zeige 5 geänderte Dateien mit 23 Einfügungen und 30 Löschungen.
git-svn-id: https://svn.discofish.de/MATLAB/spmtoolbox/SVMCrossVal@173 83ab2cfd-5345-466c-8aeb-2b2739fb922d
- private/main.m 024e928..734814f
- private/som_decode.m fbacd72..78d6d7e
- private/som_train.m c631b60..b385193
- private/som_xsubject_performance.m ae3095e..33ed85f
- private/train_som.m 6b7f3b7..0000000
| ... | ... |
@@ -135,8 +135,8 @@ switch task |
| 135 | 135 |
display('SOM');
|
| 136 | 136 |
disp('not implemented')
|
| 137 | 137 |
|
| 138 |
- case 'X-SOM' |
|
| 139 |
- display('X-SOM');
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|
| 138 |
+ case 'XSOM' |
|
| 139 |
+ display('XSOM');
|
|
| 140 | 140 |
somopts.size = [3 3]; |
| 141 | 141 |
somopts.lattice = 'rect'; |
| 142 | 142 |
decode = som_xsubject_performance(header,data,somopts); |
| ... | ... |
@@ -1,6 +1,21 @@ |
| 1 |
-function decode = som_decode(sD, sM, svm_validation_data,svm_validation_label) |
|
| 1 |
+function decode = som_decode(sM, svm_validation_data,svm_validation_label) |
|
| 2 | 2 |
% the number of hits in each map-unit. |
| 3 | 3 |
|
| 4 |
-sValD = som_data_struct(svm_validation_data,'label',num2str(svm_validation_label)); |
|
| 5 |
-h = som_hits(sM,sValD); |
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| 4 |
+sValD = som_data_struct(svm_validation_data,'labels',num2str(svm_validation_label)); |
|
| 5 |
+% h = som_hits(sM,sValD); |
|
| 6 | 6 |
bmu = som_bmus(sM, sValD, 'best'); |
| 7 |
+ |
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| 8 |
+correct = 0; |
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| 9 |
+nElements = length(svm_validation_label); |
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| 10 |
+nBMUs = length(bmu); |
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| 11 |
+ |
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| 12 |
+for i = 1:nBMUs |
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| 13 |
+ if isnan(bmu(i)) |
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| 14 |
+ nElements = nElements - 1; |
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| 15 |
+ elseif ( cell2mat(sM.labels(bmu(i))) == cell2mat(sValD.labels(i)) ) |
|
| 16 |
+ correct = correct + 1; |
|
| 17 |
+ end |
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| 18 |
+end |
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| 19 |
+ |
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| 20 |
+decode = correct/nElements*100; |
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| 21 |
+end |
|
| 7 | 22 |
\ No newline at end of file |
| ... | ... |
@@ -3,15 +3,10 @@ function [sD sM] = som_train(svmlabel, svmdata, somOptions) |
| 3 | 3 |
som_size = somOptions.size; |
| 4 | 4 |
som_lattice = somOptions.lattice; |
| 5 | 5 |
|
| 6 |
-display('SOM TRAINING');
|
|
| 7 | 6 |
addpath 'somtoolbox2'; |
| 8 |
-sD = som_data_struct(svmdata,'label',num2str(svmlabel)); |
|
| 9 |
-assignin('base','sD',sD);
|
|
| 10 |
-sM = som_make(sD,'msize', som_size,'lattice', som_lattice); |
|
| 7 |
+sD = som_data_struct(svmdata,'labels',num2str(svmlabel)); |
|
| 11 | 8 |
|
| 9 |
+sM = som_make(sD,'msize', som_size,'lattice', som_lattice); |
|
| 12 | 10 |
sM = som_autolabel(sM,sD,'vote'); |
| 13 | 11 |
|
| 14 |
-assignin('base','sD',sD);
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|
| 15 |
-assignin('base','sM',sM);
|
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| 16 |
-display('type ''figure'' before visualisation');
|
|
| 17 | 12 |
end |
| 18 | 13 |
\ No newline at end of file |
| ... | ... |
@@ -67,7 +67,7 @@ for timeIndex = 1:timeLineEnd-timeLineStart+1 |
| 67 | 67 |
|
| 68 | 68 |
[sD sM] = som_train(svm_train_label, svm_train_data, somOpts); |
| 69 | 69 |
|
| 70 |
- performance = som_decode(sD, sM, svm_validation_data,svm_validation_label); |
|
| 70 |
+ performance = som_decode(sM, svm_validation_data,svm_validation_label); |
|
| 71 | 71 |
|
| 72 | 72 |
cross_value = [cross_value performance]; |
| 73 | 73 |
end |
| ... | ... |
@@ -1,17 +0,0 @@ |
| 1 |
-function [sD sM] = train_som(svmlabel, svmdata, somOptions) |
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| 2 |
- |
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| 3 |
-som_size = somOptions.size; |
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| 4 |
-som_lattice = somOptions.lattice; |
|
| 5 |
- |
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| 6 |
-display('SOM TRAINING');
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|
| 7 |
-addpath 'somtoolbox2'; |
|
| 8 |
-sD = som_data_struct(svmdata,'label',num2str(svmlabel)); |
|
| 9 |
-assignin('base','sD',sD);
|
|
| 10 |
-sM = som_make(sD,'msize', som_size,'lattice', som_lattice); |
|
| 11 |
- |
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| 12 |
-sM = som_autolabel(sM,sD,'vote'); |
|
| 13 |
- |
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| 14 |
-assignin('base','sD',sD);
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| 15 |
-assignin('base','sM',sM);
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| 16 |
-display('type ''figure'' before visualisation');
|
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| 17 |
-end |
|
| 18 | 0 |
\ No newline at end of file |
| 19 | 1 |