[EVALUATION OF OUR CODE] : Now we have the accuracy of each approch and we can...

[EVALUATION OF OUR CODE] : Now we have the accuracy of each approch and we can compare with SKLearn accuracy

ANN/src/ann_cpp_music_style.cpp

@@ -102,16 +102,6 @@ double evaluate (std::vector<int>& truth_value, std::vector<int>& predicted_valu
     }
 }
 
-//
-//int main()
-//{
-//    std::filesystem::path fileName = "../../DATASETS/Music/blues/blues.00088.au";
-//    auto bins = compute_features_for(fileName);
-//    auto featuring = bins.begin()->second;
-//    std::cout << "cart_predict(feature) : " << std::endl<<ann_predict(featuring) <<  std::endl;
-//    return 0;
-//}
-
 int main(){
 
     std::ifstream   file("../../DATASETS/path_test_files_ANN.csv");