Function sparse_predict

src/thundersvm/thundersvm-scikit.cpp:130–143

    }

    int sparse_predict(int row_size, float* val, int* row_ptr, int* col_ptr, SvmModel *model, float* predict_label, int verbose){
        if(verbose)
            el::Loggers::reconfigureAllLoggers(el::ConfigurationType::Enabled, "true");
        else
            el::Loggers::reconfigureAllLoggers(el::ConfigurationType::Enabled, "false");
        DataSet predict_dataset;
        predict_dataset.load_from_sparse(row_size, val, row_ptr, col_ptr, (float *)NULL);
        vector<float_type> predict_y;
        predict_y = model->predict(predict_dataset.instances(), -1);
        for (int i = 0; i < predict_y.size(); ++i) {
            predict_label[i] = predict_y[i];
        }
        return 0;
    }

    void dense_model_scikit(int row_size, int features, float* data, float* label,
                                 int svm_type, int kernel_type, int degree, float gamma, float coef0,