bayes_clf.hpp

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#ifndef BAYES_CLF_HPP
#define BAYES_CLF_HPP
#include <map>
#include <string>
#include <unordered_map>
#include <vector>
 
namespace gpmp {
 
namespace ml {
 
class BayesClf {
  public:
    double alpha;
 
    bool fit_prior;
    std::unordered_map<std::string, double> class_probs;
    std::unordered_map<std::string, std::vector<double>> feature_probs;
    std::vector<double> class_log_prior;
 
    BayesClf(double alpha_param = 1.0,
             bool fit_prior_param = true,
             const std::vector<double> &class_prior = {});
 
    ~BayesClf();
    void train(const std::vector<std::vector<double>> &data,
               const std::vector<std::string> &labels);
 
    std::string predict(const std::vector<double> &newData) const;
 
    void display() const;
};
 
class BayesBernoulli {
  public:
    std::unordered_map<std::string, double> class_probs;
    std::unordered_map<std::string, std::unordered_map<size_t, double>>
        feat_probs;
    double alpha;
 
    BayesBernoulli(double alpha_param = 1.0) : alpha(alpha_param) {
    }
 
    ~BayesBernoulli() {
    }
 
    void train(const std::vector<std::vector<size_t>> &data,
               const std::vector<std::string> &labels);
    std::string predict(const std::vector<size_t> &newData) const;
 
    void display() const;
};
 
class BayesGauss {
  public:
    std::unordered_map<std::string, double> class_probs;
    std::unordered_map<std::string, std::vector<double>> mean;
    std::unordered_map<std::string, std::vector<double>> variance;
 
    BayesGauss() = default;
 
    ~BayesGauss() = default;
 
    void train(const std::vector<std::vector<double>> &data,
               const std::vector<std::string> &labels);
 
    std::string predict(const std::vector<double> &newData) const;
 
    void display() const;
 
  private:
    void mean_and_var(const std::vector<std::vector<double>> &data,
                      const std::vector<std::string> &labels);
};
 
class BayesMultiNom {
  public:
    double alpha;
    bool fit_prior;
    std::unordered_map<std::string, double> class_probs;
    std::unordered_map<std::string, std::vector<double>> feature_probs;
    std::vector<double> class_log_prior;
 
    BayesMultiNom(double alpha_param = 1.0,
                  bool fit_prior_param = true,
                  const std::vector<double> &class_prior = {});
 
    ~BayesMultiNom();
 
    void train(const std::vector<std::vector<size_t>> &data,
               const std::vector<std::string> &labels);
 
    std::string predict(const std::vector<size_t> &new_data) const;
 
    void display() const;
};
 
} // namespace ml
 
} // namespace gpmp
 
#endif