Add new hyperparameters to the Ld classifiers

- *ld_algorithm*: algorithm to use for local discretization, with the following options: "MDLP", "BINQ", "BINU".
  - *ld_proposed_cuts*: number of cut points to return.
  - *mdlp_min_length*: minimum length of a partition in MDLP algorithm to be evaluated for partition.
  - *mdlp_max_depth*: maximum level of recursion in MDLP algorithm.

bayesnet/classifiers/KDBLd.h

@@ -11,12 +11,12 @@
 
 namespace bayesnet {
     class KDBLd : public KDB, public Proposal {
-    private:
     public:
         explicit KDBLd(int k);
         virtual ~KDBLd() = default;
         KDBLd& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, map<std::string, std::vector<int>>& states, const Smoothing_t smoothing) override;
         std::vector<std::string> graph(const std::string& name = "KDB") const override;
+        void setHyperparameters(const nlohmann::json& hyperparameters_) override;
         torch::Tensor predict(torch::Tensor& X) override;
         torch::Tensor predict_proba(torch::Tensor& X) override;
         static inline std::string version() { return "0.0.1"; };