Implement the proba branch and begin with the voting one

src/Proposal.h

@@ -0,0 +1,30 @@
+#ifndef PROPOSAL_H
+#define PROPOSAL_H
+#include <string>
+#include <map>
+#include <torch/torch.h>
+#include "Network.h"
+#include "CPPFImdlp.h"
+#include "Classifier.h"
+
+namespace bayesnet {
+    class Proposal {
+    public:
+        Proposal(torch::Tensor& pDataset, std::vector<std::string>& features_, std::string& className_);
+        virtual ~Proposal();
+    protected:
+        void checkInput(const torch::Tensor& X, const torch::Tensor& y);
+        torch::Tensor prepareX(torch::Tensor& X);
+        map<std::string, std::vector<int>> localDiscretizationProposal(const map<std::string, std::vector<int>>& states, Network& model);
+        map<std::string, std::vector<int>> fit_local_discretization(const torch::Tensor& y);
+        torch::Tensor Xf; // X continuous nxm tensor
+        torch::Tensor y; // y discrete nx1 tensor
+        map<std::string, mdlp::CPPFImdlp*> discretizers;
+    private:
+        torch::Tensor& pDataset; // (n+1)xm tensor
+        std::vector<std::string>& pFeatures;
+        std::string& pClassName;
+    };
+}
+
+#endif