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It is now possible to make certain expressions more important when training SVM models.

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This commit is contained in:
Emiliana 2020-03-07 13:35:58 +01:00
parent 94d2f4fbe0
commit 9aeb4fe95d
5 changed files with 56 additions and 20 deletions
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17
Source/SVMWrapper.cpp
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@ -87,7 +87,7 @@ void destroy_problem(struct svm_problem *problem) {
}
extern "C" {
__declspec(dllexport) void *__cdecl trainModel(float features[], float labels[], int rows, int cols, int classes, int probability, float C) {
__declspec(dllexport) void *__cdecl trainModel(float features[], float labels[], float weights[], int rows, int cols, int classes, int probability, float C) {
if (!(rows > 0 && cols > 0))
return NULL;
@ -115,10 +115,25 @@ extern "C" {
sw->param.weight_label = NULL;
sw->param.weight = NULL;
if (weights != NULL) {
sw->param.nr_weight = classes;
sw->param.weight_label = new int[classes];
sw->param.weight = new double[classes];
for (int i = 0; i < classes; i++) {
sw->param.weight_label[i] = i;
sw->param.weight[i] = (double)weights[i];
}
}
sw->problem = new struct svm_problem();
make_problem(sw->problem, features, labels, rows, cols, sw->means, sw->sdevs);
sw->model = svm_train(sw->problem, &sw->param);
if (weights != NULL) {
delete sw->param.weight_label;
delete sw->param.weight;
}
return sw;
}