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Complete refactor of XA1DE & XBAODE with new ExpClf class

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This commit is contained in:
Ricardo Montañana Gómez
2025-02-26 16:55:04 +01:00
parent c63baf419f
commit 1a688f90b4
7 changed files with 319 additions and 402 deletions
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47
src/experimental_clfs/Xaode.hpp
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@@ -16,6 +16,7 @@
#include <string>
#include <cmath>
#include <limits>
#include <torch/torch.h>
namespace platform {
class Xaode {
@@ -28,11 +29,49 @@ namespace platform {
COUNTS,
PROBS
};
double duration_first = 0.0;
double duration_second = 0.0;
double duration_third = 0.0;
std::vector<double> significance_models;
Xaode() : nFeatures_{ 0 }, statesClass_{ 0 }, matrixState_{ MatrixState::EMPTY } {}
// -------------------------------------------------------
// fit
// -------------------------------------------------------
//
// Classifiers interface
// all parameter decide if the model is initialized with all the parents active or none of them
//
void 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 torch::Tensor& weights, const bool all_parents)
{
int num_instances = X[0].size();
int n_features_ = X.size();
significance_models.resize(n_features_, (all_parents ? 1.0 : 0.0));
std::vector<int> statesv;
for (int i = 0; i < n_features_; i++) {
if (all_parents) active_parents.push_back(i);
statesv.push_back(*max_element(X[i].begin(), X[i].end()) + 1);
}
statesv.push_back(*max_element(y.begin(), y.end()) + 1);
// std::cout << "* States: " << statesv << std::endl;
// std::cout << "* Weights: " << weights_ << std::endl;
// std::cout << "* Instances: " << num_instances << std::endl;
// std::cout << "* Attributes: " << n_features_ +1 << std::endl;
// std::cout << "* y: " << y << std::endl;
// std::cout << "* x shape: " << X.size() << "x" << X[0].size() << std::endl;
// for (int i = 0; i < n_features_; i++) {
// std::cout << "* " << features[i] << ": " << instances[i] << std::endl;
// }
// std::cout << "Starting to build the model" << std::endl;
init(statesv);
std::vector<int> instance(n_features_ + 1);
for (int n_instance = 0; n_instance < num_instances; n_instance++) {
for (int feature = 0; feature < n_features_; feature++) {
instance[feature] = X[feature][n_instance];
}
instance[n_features_] = y[n_instance];
addSample(instance, weights[n_instance].item<double>());
}
computeProbabilities();
}
// -------------------------------------------------------
// init
// -------------------------------------------------------
//
@@ -406,7 +445,7 @@ namespace platform {
{
return (nFeatures_ + 1) * nFeatures_;
}
void set_active_parent(int active_parent)
void add_active_parent(int active_parent)
{
active_parents.push_back(active_parent);
}