print metric for cross-validation

Xtra-Computing · Jun 14, 2018 · f747325 · f747325
1 parent 22651ce
commit f747325
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Showing 2 changed files with 19 additions and 17 deletions.
diff --git a/src/thundersvm/model/svmmodel.cpp b/src/thundersvm/model/svmmodel.cpp
@@ -33,7 +33,7 @@ vector<float_type> SvmModel::cross_validation(DataSet dataset, SvmParam param, i
     vector<float_type> y_predict_all(dataset.n_instances());
 
     for (int k = 0; k < n_fold; ++k) {
-        LOG(INFO) << n_fold << " fold cross-validation(" << k + 1 << "/" << n_fold << ")";
+        LOG(INFO) << n_fold << " fold cross-validation (" << k + 1 << "/" << n_fold << ")";
         DataSet::node2d x_train, x_test;
         vector<float_type> y_train, y_test;
         vector<int> test_idx;

diff --git a/src/thundersvm/thundersvm-train.cpp b/src/thundersvm/thundersvm-train.cpp
@@ -90,25 +90,27 @@ int main(int argc, char **argv) {
         }
 
         //perform svm testing
-        /*std::shared_ptr<Metric> metric;
-        switch (parser.param_cmd.svm_type) {
-            case SvmParam::C_SVC:
-            case SvmParam::NU_SVC: {
-                metric.reset(new Accuracy());
-                break;
-            }
-            case SvmParam::EPSILON_SVR:
-            case SvmParam::NU_SVR: {
-                metric.reset(new MSE());
-                break;
+        if(parser.do_cross_validation) {
+            std::shared_ptr<Metric> metric;
+            switch (parser.param_cmd.svm_type) {
+                case SvmParam::C_SVC:
+                case SvmParam::NU_SVC: {
+                    metric.reset(new Accuracy());
+                    break;
+                }
+                case SvmParam::EPSILON_SVR:
+                case SvmParam::NU_SVR: {
+                    metric.reset(new MSE());
+                    break;
+                }
+                case SvmParam::ONE_CLASS: {
+                }
             }
-            case SvmParam::ONE_CLASS: {
+            if (metric) {
+                std::cout << metric->name() << " = " << metric->score(predict_y, train_dataset.y()) << std::endl;
             }
         }
-        if (metric) {
-            std::cout << metric->name() << " = " << metric->score(predict_y, train_dataset.y()) << std::endl;
-        }
-		*/
+
     }
     catch (std::bad_alloc &) {
         LOG(FATAL) << "out of memory, you may try \"-m memory size\" to constrain memory usage";