Begin implementation

src/Platform/Datasets.cc

@@ -207,9 +207,9 @@ namespace platform {
         if (discretize) {
             Xd = discretizeDataset(Xv, yv);
             computeStates();
-            n_samples = Xd[0].size();
-            n_features = Xd.size();
         }
+        n_samples = Xv[0].size();
+        n_features = Xv.size();
         loaded = true;
     }
     void Dataset::buildTensors()

src/Platform/Experiment.cc

@@ -104,7 +104,7 @@ namespace platform {
 
     void Experiment::cross_validation(const string& path, const string& fileName)
     {
-        auto datasets = platform::Datasets(path, true, platform::ARFF);
+        auto datasets = platform::Datasets(path, discretized, platform::ARFF);
         // Get dataset
         auto [X, y] = datasets.getTensors(fileName);
         auto states = datasets.getStates(fileName);

src/Platform/Models.h

@@ -6,6 +6,7 @@
 #include "TAN.h"
 #include "KDB.h"
 #include "SPODE.h"
+#include "TANNew.h"
 namespace platform {
     class Models {
     private:

src/Platform/modelRegister.h

@@ -2,6 +2,8 @@
 #define MODEL_REGISTER_H
 static platform::Registrar registrarT("TAN",
     [](void) -> bayesnet::BaseClassifier* { return new bayesnet::TAN();});
+static platform::Registrar registrarTN("TANNew",
+    [](void) -> bayesnet::BaseClassifier* { return new bayesnet::TANNew();});
 static platform::Registrar registrarS("SPODE",
     [](void) -> bayesnet::BaseClassifier* { return new bayesnet::SPODE(2);});
 static platform::Registrar registrarK("KDB",