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This commit is contained in:
Ricardo Montañana Gómez
2025-02-26 21:03:01 +01:00
parent 1a688f90b4
commit 0d1e4b3c6f
5 changed files with 17 additions and 14 deletions
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4
src/CMakeLists.txt
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@@ -28,6 +28,7 @@ add_executable(
results/Result.cpp
experimental_clfs/XA1DE.cpp
experimental_clfs/XBAODE.cpp
experimental_clfs/ExpClf.cpp
)
target_link_libraries(b_best Boost::boost "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy "${XLSXWRITER_LIB}")
@@ -41,6 +42,7 @@ add_executable(b_grid commands/b_grid.cpp ${grid_sources}
results/Result.cpp
experimental_clfs/XA1DE.cpp
experimental_clfs/XBAODE.cpp
experimental_clfs/ExpClf.cpp
)
target_link_libraries(b_grid ${MPI_CXX_LIBRARIES} "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy)
@@ -52,6 +54,7 @@ add_executable(b_list commands/b_list.cpp
results/Result.cpp results/ResultsDatasetExcel.cpp results/ResultsDataset.cpp results/ResultsDatasetConsole.cpp
experimental_clfs/XA1DE.cpp
experimental_clfs/XBAODE.cpp
experimental_clfs/ExpClf.cpp
)
target_link_libraries(b_list "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy "${XLSXWRITER_LIB}")
@@ -64,6 +67,7 @@ add_executable(b_main commands/b_main.cpp ${main_sources}
results/Result.cpp
experimental_clfs/XA1DE.cpp
experimental_clfs/XBAODE.cpp
experimental_clfs/ExpClf.cpp
)
target_link_libraries(b_main "${PyClassifiers}" "${BayesNet}" fimdlp ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} Boost::python Boost::numpy)

2
src/experimental_clfs/ExpClf.cpp
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@@ -8,7 +8,7 @@
#include "TensorUtils.hpp"
namespace platform {
ExpClf::ExpClf() : semaphore_{ CountingSemaphore::getInstance() }
ExpClf::ExpClf() : semaphore_{ CountingSemaphore::getInstance() }, Boost(false)
{
}
void ExpClf::setHyperparameters(const nlohmann::json& hyperparameters)

4
src/experimental_clfs/ExpClf.h
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@@ -12,14 +12,14 @@
#include <cmath>
#include <algorithm>
#include <limits>
#include "bayesnet/BaseClassifier.h"
#include "bayesnet/ensembles/Boost.h"
#include "common/Timer.hpp"
#include "CountingSemaphore.hpp"
#include "Xaode.hpp"
namespace platform {
class ExpClf : public bayesnet::BaseClassifier {
class ExpClf : public bayesnet::Boost {
public:
ExpClf();
virtual ~ExpClf() = default;

18
src/experimental_clfs/XBAODE.cpp
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@@ -13,14 +13,14 @@
#include <loguru.hpp>
namespace platform {
XBAODE::XBAODE() : Boost(false)
XBAODE::XBAODE()
{
Boost::validHyperparameters = { "alpha_block", "order", "convergence", "convergence_best", "bisection", "threshold", "maxTolerance",
validHyperparameters = { "alpha_block", "order", "convergence", "convergence_best", "bisection", "threshold", "maxTolerance",
"predict_voting", "select_features" };
}
void XBAODE::trainModel(const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing)
{
Boost::fitted = true;
fitted = true;
X_train_ = TensorUtils::to_matrix(X_train);
y_train_ = TensorUtils::to_vector<int>(y_train);
X_test_ = TensorUtils::to_matrix(X_test);
@@ -44,7 +44,7 @@ namespace platform {
if (selectFeatures) {
featuresUsed = featureSelection(weights_);
set_active_parents(featuresUsed);
Boost::notes.push_back("Used features in initialization: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()) + " with " + select_features_algorithm);
notes.push_back("Used features in initialization: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()) + " with " + select_features_algorithm);
auto ypred = ExpClf::predict(X_train);
std::tie(weights_, alpha_t, finished) = update_weights(y_train, ypred, weights_);
// Update significance of the models
@@ -146,7 +146,7 @@ namespace platform {
}
if (tolerance > maxTolerance) {
if (numItemsPack < n_models) {
Boost::notes.push_back("Convergence threshold reached & " + std::to_string(numItemsPack) + " models eliminated");
notes.push_back("Convergence threshold reached & " + std::to_string(numItemsPack) + " models eliminated");
VLOG_SCOPE_F(4, "Convergence threshold reached & %d models eliminated of %d", numItemsPack, n_models);
for (int i = featuresUsed.size() - 1; i >= featuresUsed.size() - numItemsPack; --i) {
aode_.remove_last_parent();
@@ -155,15 +155,15 @@ namespace platform {
}
VLOG_SCOPE_F(4, "*Convergence threshold %d models left & %d features used.", n_models, featuresUsed.size());
} else {
Boost::notes.push_back("Convergence threshold reached & 0 models eliminated");
notes.push_back("Convergence threshold reached & 0 models eliminated");
VLOG_SCOPE_F(4, "Convergence threshold reached & 0 models eliminated n_models=%d numItemsPack=%d", n_models, numItemsPack);
}
}
if (featuresUsed.size() != features.size()) {
Boost::notes.push_back("Used features in train: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()));
Boost::status = bayesnet::WARNING;
notes.push_back("Used features in train: " + std::to_string(featuresUsed.size()) + " of " + std::to_string(features.size()));
status = bayesnet::WARNING;
}
Boost::notes.push_back("Number of models: " + std::to_string(n_models));
notes.push_back("Number of models: " + std::to_string(n_models));
return;
}
}

3
src/experimental_clfs/XBAODE.h
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@@ -12,11 +12,10 @@
#include <algorithm>
#include <limits>
#include "common/Timer.hpp"
#include "bayesnet/ensembles/Boost.h"
#include "ExpClf.h"
namespace platform {
class XBAODE : public bayesnet::Boost, public ExpClf {
class XBAODE : public ExpClf {
public:
XBAODE();
virtual ~XBAODE() = default;