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Fix classifier build in proposal

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Ricardo Montañana Gómez
2025-07-07 02:10:08 +02:00
parent 0ce7f664b4
commit 2c7352ac38
7 changed files with 29 additions and 16 deletions
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28
bayesnet/classifiers/Proposal.cc
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@@ -8,6 +8,11 @@
#include <iostream>
#include <cmath>
#include <limits>
#include "Classifier.h"
#include "KDB.h"
#include "TAN.h"
#include "KDBLd.h"
#include "TANLd.h"
namespace bayesnet {
Proposal::Proposal(torch::Tensor& dataset_, std::vector<std::string>& features_, std::string& className_) : pDataset(dataset_), pFeatures(features_), pClassName(className_)
@@ -180,7 +185,7 @@ namespace bayesnet {
map<std::string, std::vector<int>> Proposal::iterativeLocalDiscretization(
const torch::Tensor& y,
Classifier* classifier,
const torch::Tensor& dataset,
torch::Tensor& dataset,
const std::vector<std::string>& features,
const std::string& className,
const map<std::string, std::vector<int>>& initialStates,
@@ -196,19 +201,20 @@ namespace bayesnet {
<< convergence_params.maxIterations << " max iterations" << std::endl;
}
const torch::Tensor weights = torch::full({ pDataset.size(1) }, 1.0 / pDataset.size(1), torch::kDouble);
for (int iteration = 0; iteration < convergence_params.maxIterations; ++iteration) {
if (convergence_params.verbose) {
std::cout << "Iteration " << (iteration + 1) << "/" << convergence_params.maxIterations << std::endl;
}
// Phase 2: Build model with current discretization
classifier->fit(dataset, features, className, currentStates, smoothing);
classifier->fit(dataset, features, className, currentStates, weights, smoothing);
// Phase 3: Network-aware discretization refinement
currentStates = localDiscretizationProposal(currentStates, classifier->model);
currentStates = localDiscretizationProposal(currentStates, classifier->getModel());
// Check convergence
if (iteration > 0 && previousModel == classifier->model) {
if (iteration > 0 && previousModel == classifier->getModel()) {
if (convergence_params.verbose) {
std::cout << "Converged after " << (iteration + 1) << " iterations" << std::endl;
}
@@ -216,7 +222,7 @@ namespace bayesnet {
}
// Update for next iteration
previousModel = classifier->model;
previousModel = classifier->getModel();
}
return currentStates;
@@ -262,7 +268,11 @@ namespace bayesnet {
}
// Explicit template instantiation for common classifier types
// template map<std::string, std::vector<int>> Proposal::iterativeLocalDiscretization<Classifier>(
// const torch::Tensor&, Classifier*, const torch::Tensor&, const std::vector<std::string>&,
// const std::string&, const map<std::string, std::vector<int>>&, Smoothing_t);
template map<std::string, std::vector<int>> Proposal::iterativeLocalDiscretization<KDB>(
const torch::Tensor&, KDB*, torch::Tensor&, const std::vector<std::string>&,
const std::string&, const map<std::string, std::vector<int>>&, Smoothing_t);
template map<std::string, std::vector<int>> Proposal::iterativeLocalDiscretization<TAN>(
const torch::Tensor&, TAN*, torch::Tensor&, const std::vector<std::string>&,
const std::string&, const map<std::string, std::vector<int>>&, Smoothing_t);
}