Fix some small mistakes

bayesclass/BaseClassifier.cc

@@ -8,7 +8,7 @@ namespace bayesnet {
     BaseClassifier& BaseClassifier::build(vector<string>& features, string className, map<string, vector<int>>& states)
     {
 
-        dataset = torch::cat({ X, y.view({150, 1}) }, 1);
+        dataset = torch::cat({ X, y.view({y.size(0), 1}) }, 1);
         this->features = features;
         this->className = className;
         this->states = states;
@@ -86,8 +86,8 @@ namespace bayesnet {
         Tensor y_pred = predict(X);
         return (y_pred == y).sum().item<float>() / y.size(0);
     }
-    void BaseClassifier::show()
+    vector<string> BaseClassifier::show()
     {
-        model.show();
+        return model.show();
     }
 }

bayesclass/BaseClassifier.h

@@ -28,9 +28,8 @@ namespace bayesnet {
         BaseClassifier& fit(vector<vector<int>>& X, vector<int>& y, vector<string>& features, string className, map<string, vector<int>>& states);
         Tensor predict(Tensor& X);
         float score(Tensor& X, Tensor& y);
-        void show();
+        vector<string> show();
     };
-
 }
 #endif
 

bayesclass/KDB.h

@@ -10,9 +10,9 @@ namespace bayesnet {
         float theta;
         void add_m_edges(int idx, vector<int>& S, Tensor& weights);
     protected:
-        void train();
+        void train() override;
     public:
-        KDB(int k, float theta=0.03);
+        KDB(int k, float theta = 0.03);
     };
 }
 #endif

bayesclass/Network.cc

@@ -245,16 +245,18 @@ namespace bayesnet {
         }
         return result;
     }
-    void Network::show()
+    vector<string> Network::show()
     {
+        vector<string> result;
         // Draw the network
         for (auto node : nodes) {
-            cout << node.first << " -> ";
+            string line = node.first + " -> ";
             for (auto child : node.second->getChildren()) {
-                cout << child->getName() << ", ";
+                line += child->getName() + ", ";
             }
-            cout << endl;
+            result.push_back(line);
         }
+        return result;
     }
 
 }

bayesclass/Network.h

@@ -44,7 +44,7 @@ namespace bayesnet {
         torch::Tensor conditionalEdgeWeight();
         vector<vector<double>> predict_proba(const vector<vector<int>>&);
         double score(const vector<vector<int>>&, const vector<int>&);
-        void show();
+        vector<string> show();
         inline string version() { return "0.1.0"; }
     };
 }