Create XBAODE classifier

2025-02-23 19:44:13 +01:00
parent 1b26de1e38
commit 5daf7cbd69
7 changed files with 210 additions and 41 deletions
--- a/src/experimental_clfs/XBAODE.h
+++ b/src/experimental_clfs/XBAODE.h
@@ -0,0 +1,67 @@
+// ***************************************************************
+// SPDX-FileCopyrightText: Copyright 2025 Ricardo Montañana Gómez
+// SPDX-FileType: SOURCE
+// SPDX-License-Identifier: MIT
+// ***************************************************************
+
+#ifndef XBAODE_H
+#define XBAODE_H
+#include <iostream>
+#include <vector>
+#include <cmath>
+#include <algorithm>
+#include <limits>
+#include "common/Timer.hpp"
+#include "CountingSemaphore.hpp"
+#include "bayesnet/ensembles/Boost.h"
+#include "XA1DE.h"
+
+namespace platform {
+
+    class XBAODE : public bayesnet::Boost {
+    public:
+        XBAODE();
+        virtual ~XBAODE() = default;
+        const std::string CLASSIFIER_NOT_FITTED = "Classifier has not been fitted";
+
+        XBAODE& fit(std::vector<std::vector<int>>& X, std::vector<int>& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
+        XBAODE& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
+        XBAODE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
+        XBAODE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override;
+        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<std::vector<double>> predict_proba_threads(const std::vector<std::vector<int>>& test_data);
+        std::vector<std::vector<double>> predict_proba(std::vector<std::vector<int>>& X) override;
+        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;
+        bayesnet::status_t getStatus() const override { return status; }
+        std::string getVersion() override { return version; };
+        std::vector<std::string> show() const override { return {}; }
+        std::vector<std::string> topological_order()  override { return {}; }
+        std::vector<std::string> getNotes() const override { return notes; }
+        std::string dump_cpt() const override { return ""; }
+        std::vector<std::string>& getValidHyperparameters() { return validHyperparameters; }
+        void setDebug(bool debug) { this->debug = debug; }
+        std::vector<std::string> graph(const std::string& title = "") const override { return {}; }
+        void set_active_parents(std::vector<int> active_parents) { aode_.set_active_parents(active_parents); }
+    protected:
+        void trainModel(const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override {};
+
+    private:
+        XA1DE aode_;
+        std::vector<double> weights_;
+        CountingSemaphore& semaphore_;
+        bool debug = false;
+        bayesnet::status_t status = bayesnet::NORMAL;
+        std::vector<std::string> notes;
+        bool use_threads = true;
+        std::string version = "0.9.7";
+        bool fitted = false;
+    };
+}
+#endif // XBAODE_H