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It is now possible to train expression models with probability support. This however is a lot slower! Also, the C parameter for SVM training was set incorrectly. Now training works much better.

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This commit is contained in:
Emiliana 2020-02-13 22:24:41 +01:00
parent 9abc3029e7
commit bb845098ca
4 changed files with 46 additions and 20 deletions
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20
Source/SVMWrapper.cpp
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@ -15,6 +15,7 @@ extern "C" void __cdecl print_log(const char *str) {
struct SVMWrapper {
struct svm_model *model;
int cols;
int classes;
double *means;
double *sdevs;
struct svm_parameter param;
@ -86,7 +87,7 @@ void destroy_problem(struct svm_problem *problem) {
}
extern "C" {
__declspec(dllexport) void *__cdecl trainModel(float features[], float labels[], int rows, int cols) {
__declspec(dllexport) void *__cdecl trainModel(float features[], float labels[], int rows, int cols, int classes, int probability, float C) {
if (!(rows > 0 && cols > 0))
return NULL;
@ -94,6 +95,7 @@ extern "C" {
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
@ -104,11 +106,11 @@ extern "C" {
sw->param.coef0 = 0;
sw->param.nu = 0.5;
sw->param.cache_size = 100;
sw->param.C = 4;
sw->param.C = C;
sw->param.eps = 0.001;
sw->param.p = 0.1;
sw->param.shrinking = 1;
sw->param.probability = 0;
sw->param.probability = probability;
sw->param.nr_weight = 0;
sw->param.weight_label = NULL;
sw->param.weight = NULL;
@ -120,22 +122,23 @@ extern "C" {
return sw;
}
__declspec(dllexport) void __cdecl predict(void *ptr, float features[], float predictions[], int rows) {
__declspec(dllexport) void __cdecl predict(void *ptr, float features[], float predictions[], double probabilities[], int rows) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
int cols = sw->cols;
svmnode **x = make_svmnode_array(features, rows, cols, sw->means, sw->sdevs, 0);
for (int r = 0; r < rows; r++)
predictions[r] = (float)svm_predict(sw->model, x[r]);
predictions[r] = (float)svm_predict_probability(sw->model, x[r], &(probabilities[r * sw->classes]));
destroy_svmnode_array(x);
return;
}
__declspec(dllexport) void *__cdecl loadModel(char *filename, int cols, double means[], double sdevs[]) {
__declspec(dllexport) void *__cdecl loadModel(char *filename, int cols, int classes, double means[], double sdevs[]) {
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->model = svm_load_model(filename);
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
for (int c = 0; c < cols; c++) {
@ -145,10 +148,11 @@ extern "C" {
return sw;
}
__declspec(dllexport) void *__cdecl loadModelString(char *modelString, int cols, double means[], double sdevs[]) {
__declspec(dllexport) void *__cdecl loadModelString(char *modelString, int cols, int classes, double means[], double sdevs[]) {
struct SVMWrapper *sw = new SVMWrapper();
sw->cols = cols;
sw->model = svm_load_model_string(modelString);
sw->classes = classes;
sw->means = new double[cols];
sw->sdevs = new double[cols];
for (int c = 0; c < cols; c++) {
@ -168,7 +172,7 @@ extern "C" {
}
}
__declspec(dllexport) char *__cdecl getModel(void *ptr) {
__declspec(dllexport) char *__cdecl saveModelString (void *ptr) {
struct SVMWrapper *sw = (struct SVMWrapper *)ptr;
return svm_save_model_string(sw->model);
}