Begin to add AdaBoost implementation

src/experimental_clfs/AdaBoost.h

@@ -0,0 +1,58 @@
+// ***************************************************************
+// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
+// SPDX-FileType: SOURCE
+// SPDX-License-Identifier: MIT
+// ***************************************************************
+
+#ifndef ADABOOST_H
+#define ADABOOST_H
+
+#include <vector>
+#include <memory>
+#include <torch/torch.h>
+#include <bayesnet/ensembles/Ensemble.h>
+
+namespace platform {
+    class AdaBoost : public bayesnet::Ensemble {
+    public:
+        explicit AdaBoost(int n_estimators = 100);
+        virtual ~AdaBoost() = default;
+
+        // Override base class methods
+        std::vector<std::string> graph(const std::string& title = "") const override;
+
+        // AdaBoost specific methods
+        void setNEstimators(int n_estimators) { this->n_estimators = n_estimators; }
+        int getNEstimators() const { return n_estimators; }
+
+        // Get the weight of each base estimator
+        std::vector<double> getEstimatorWeights() const { return alphas; }
+
+        // Override setHyperparameters from BaseClassifier
+        void setHyperparameters(const nlohmann::json& hyperparameters) override;
+
+    protected:
+        void buildModel(const torch::Tensor& weights) override;
+        void trainModel(const torch::Tensor& weights, const Smoothing_t smoothing) override;
+
+    private:
+        int n_estimators;
+        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
+
+        // Train a single base estimator
+        std::unique_ptr<Classifier> trainBaseEstimator(const torch::Tensor& weights);
+
+        // Calculate weighted error
+        double calculateWeightedError(Classifier* estimator, const torch::Tensor& weights);
+
+        // Update sample weights based on predictions
+        void updateSampleWeights(Classifier* estimator, double alpha);
+
+        // Normalize weights to sum to 1
+        void normalizeWeights();
+    };
+}
+
+#endif // ADABOOST_H