Refactor library structure
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41
bayesnet/BaseClassifier.h
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41
bayesnet/BaseClassifier.h
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#ifndef BASE_H
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#define BASE_H
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#include <vector>
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#include <torch/torch.h>
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#include <nlohmann/json.hpp>
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namespace bayesnet {
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enum status_t { NORMAL, WARNING, ERROR };
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class BaseClassifier {
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public:
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// X is nxm std::vector, y is nx1 std::vector
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virtual BaseClassifier& 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) = 0;
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// X is nxm tensor, y is nx1 tensor
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virtual BaseClassifier& 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) = 0;
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virtual BaseClassifier& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states) = 0;
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virtual BaseClassifier& 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) = 0;
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virtual ~BaseClassifier() = default;
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torch::Tensor virtual predict(torch::Tensor& X) = 0;
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std::vector<int> virtual predict(std::vector<std::vector<int >>& X) = 0;
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torch::Tensor virtual predict_proba(torch::Tensor& X) = 0;
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std::vector<std::vector<double>> virtual predict_proba(std::vector<std::vector<int >>& X) = 0;
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status_t virtual getStatus() const = 0;
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float virtual score(std::vector<std::vector<int>>& X, std::vector<int>& y) = 0;
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float virtual score(torch::Tensor& X, torch::Tensor& y) = 0;
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int virtual getNumberOfNodes()const = 0;
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int virtual getNumberOfEdges()const = 0;
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int virtual getNumberOfStates() const = 0;
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int virtual getClassNumStates() const = 0;
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std::vector<std::string> virtual show() const = 0;
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std::vector<std::string> virtual graph(const std::string& title = "") const = 0;
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virtual std::string getVersion() = 0;
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std::vector<std::string> virtual topological_order() = 0;
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std::vector<std::string> virtual getNotes() const = 0;
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void virtual dump_cpt()const = 0;
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virtual void setHyperparameters(const nlohmann::json& hyperparameters) = 0;
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std::vector<std::string>& getValidHyperparameters() { return validHyperparameters; }
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protected:
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virtual void trainModel(const torch::Tensor& weights) = 0;
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std::vector<std::string> validHyperparameters;
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};
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}
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#endif
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