Add XBAODE & XSPODE from bayesnet

2025-03-09 19:20:51 +01:00
parent ae7b89b134
commit 664a6a5aeb
8 changed files with 302 additions and 49 deletions
--- a/src/experimental_clfs/ExpEnsemble.h
+++ b/src/experimental_clfs/ExpEnsemble.h
@@ -0,0 +1,66 @@
+// ***************************************************************
+// SPDX-FileCopyrightText: Copyright 2025 Ricardo Montañana Gómez
+// SPDX-FileType: SOURCE
+// SPDX-License-Identifier: MIT
+// ***************************************************************
+
+#ifndef EXPENSEMBLE_H
+#define EXPENSEMBLE_H
+#include <vector>
+#include <string>
+#include <cmath>
+#include <algorithm>
+#include <limits>
+#include <bayesnet/ensembles/Boost.h>
+#include <bayesnet/network/Smoothing.h>
+#include "common/Timer.hpp"
+#include "CountingSemaphore.hpp"
+#include "XSpode.hpp"
+
+namespace platform {
+    class ExpEnsemble : public bayesnet::Boost {
+    public:
+        ExpEnsemble();
+        virtual ~ExpEnsemble() = default;
+        std::vector<int> predict(std::vector<std::vector<int>>& X) override;
+        torch::Tensor predict(torch::Tensor& X) override;
+        torch::Tensor predict_proba(torch::Tensor& X) override;
+        std::vector<int> predict_spode(std::vector<std::vector<int>>& test_data, int parent);
+        std::vector<std::vector<double>> predict_proba(const std::vector<std::vector<int>>& X);
+        float score(std::vector<std::vector<int>>& X, std::vector<int>& y) override;
+        float score(torch::Tensor& X, torch::Tensor& y) override;
+        int getNumberOfNodes() const override;
+        int getNumberOfEdges() const override;
+        int getNumberOfStates() const override;
+        int getClassNumStates() const override;
+        std::vector<std::string> show() const override { return {}; }
+        std::vector<std::string> topological_order()  override { return {}; }
+        std::string dump_cpt() const override { return ""; }
+        void setDebug(bool debug) { this->debug = debug; }
+        bayesnet::status_t getStatus() const override { return status; }
+        std::vector<std::string> getNotes() const override { return notes; }
+        std::vector<std::string> graph(const std::string& title = "") const override { return {}; }
+    protected:
+        void add_model(std::unique_ptr<XSpode> model);
+        void remove_last_model();
+        bool debug = false;
+        std::vector <std::unique_ptr<XSpode>> models_;
+        torch::Tensor weights_;
+        std::vector<double> significanceModels_;
+        const std::string CLASSIFIER_NOT_FITTED = "Classifier has not been fitted";
+        inline void normalize_weights(int num_instances)
+        {
+            double sum = weights_.sum().item<double>();
+            if (sum == 0) {
+                weights_ = torch::full({ num_instances }, 1.0);
+            } else {
+                for (int i = 0; i < weights_.size(0); ++i) {
+                    weights_[i] = weights_[i].item<double>() * num_instances / sum;
+                }
+            }
+        }
+    private:
+        CountingSemaphore& semaphore_;
+    };
+}
+#endif // EXPENSEMBLE_H