Add DecisionTree with tests

src/experimental_clfs/AdaBoost.h

@@ -9,13 +9,12 @@
 
 #include <vector>
 #include <memory>
-#include <torch/torch.h>
-#include <bayesnet/ensembles/Ensemble.h>
+#include "bayesnet/ensembles/Ensemble.h"
 
-namespace platform {
-    class AdaBoost : public bayesnet::Ensemble {
+namespace bayesnet {
+    class AdaBoost : public Ensemble {
     public:
-        explicit AdaBoost(int n_estimators = 100);
+        explicit AdaBoost(int n_estimators = 50, int max_depth = 1);
         virtual ~AdaBoost() = default;
 
         // Override base class methods
@@ -24,10 +23,15 @@ namespace platform {
         // AdaBoost specific methods
         void setNEstimators(int n_estimators) { this->n_estimators = n_estimators; }
         int getNEstimators() const { return n_estimators; }
+        void setBaseMaxDepth(int depth) { this->base_max_depth = depth; }
+        int getBaseMaxDepth() const { return base_max_depth; }
 
         // Get the weight of each base estimator
         std::vector<double> getEstimatorWeights() const { return alphas; }
 
+        // Get training errors for each iteration
+        std::vector<double> getTrainingErrors() const { return training_errors; }
+
         // Override setHyperparameters from BaseClassifier
         void setHyperparameters(const nlohmann::json& hyperparameters) override;
 
@@ -37,6 +41,7 @@ namespace platform {
 
     private:
         int n_estimators;
+        int base_max_depth;  // Max depth for base decision trees
         std::vector<double> alphas;  // Weight of each base estimator
         std::vector<double> training_errors;  // Training error at each iteration
         torch::Tensor sample_weights;  // Current sample weights