src/BayesNet/BayesMetrics.cc

@@ -45,7 +45,6 @@ namespace bayesnet {
             auto mask = samples.index({ -1,  "..." }) == value;
             margin[value] = mask.sum().item<double>() / samples.size(1);
         }
-        cout << "Margin: " << margin;
         for (auto [first, second] : combinations) {
             int index_first = find(features.begin(), features.end(), first) - features.begin();
             int index_second = find(features.begin(), features.end(), second) - features.begin();

src/BayesNet/TAN.cc

@@ -22,8 +22,6 @@ namespace bayesnet {
         auto root = mi[mi.size() - 1].first;
         // 2. Compute mutual information between each feature and the class
         auto weights_matrix = metrics.conditionalEdge(weights);
-        cout << "*** Weights matrix ***\n";
-        cout << weights_matrix << "\n";
         // 3. Compute the maximum spanning tree
         auto mst = metrics.maximumSpanningTree(features, weights_matrix, root);
         // 4. Add edges from the maximum spanning tree to the model