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Bugfix: #4030 SVM auto-training.

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This commit is contained in:
Sancho McCann
2015-04-01 19:00:39 +00:00
parent 864b4e3b26
commit 6593422c05
2 changed files with 92 additions and 3 deletions
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6
modules/ml/src/svm.cpp
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@@ -1669,13 +1669,13 @@ public:
Mat samples = data->getTrainSamples();
Mat responses;
bool is_classification = false;
Mat class_labels0 = class_labels;
int class_count = (int)class_labels.total();
if( svmType == C_SVC || svmType == NU_SVC )
{
responses = data->getTrainNormCatResponses();
class_labels = data->getClassLabels();
class_count = (int)class_labels.total();
is_classification = true;
vector<int> temp_class_labels;
@@ -1755,8 +1755,9 @@ public:
Mat temp_train_responses(train_sample_count, 1, rtype);
Mat temp_test_responses;
// If grid.minVal == grid.maxVal, this will allow one and only one pass through the loop with params.var = grid.minVal.
#define FOR_IN_GRID(var, grid) \
for( params.var = grid.minVal; params.var == grid.minVal || params.var < grid.maxVal; params.var *= grid.logStep )
for( params.var = grid.minVal; params.var == grid.minVal || params.var < grid.maxVal; params.var = (grid.minVal == grid.maxVal) ? grid.maxVal + 1 : params.var * grid.logStep )
FOR_IN_GRID(C, C_grid)
FOR_IN_GRID(gamma, gamma_grid)
@@ -1814,7 +1815,6 @@ public:
}
params = best_params;
class_labels = class_labels0;
return do_train( samples, responses );
}