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Begin XBAODE tests

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This commit is contained in:
Ricardo Montañana Gómez
2025-03-11 18:16:50 +01:00
parent a59689272d
commit 71b05cc1a7
10 changed files with 678 additions and 634 deletions
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5
sample/sample.cc
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@@ -6,7 +6,7 @@
#include <ArffFiles.hpp>
#include <CPPFImdlp.h>
#include <bayesnet/ensembles/BoostAODE.h>
#include <bayesnet/ensembles/XBAODE.h>
std::vector<mdlp::labels_t> discretizeDataset(std::vector<mdlp::samples_t>& X, mdlp::labels_t& y)
{
@@ -57,7 +57,7 @@ int main(int argc, char* argv[])
std::vector<std::string> features;
std::string className;
map<std::string, std::vector<int>> states;
auto clf = bayesnet::BoostAODE(false); // false for not using voting in predict
auto clf = bayesnet::XBAODE(); // false for not using voting in predict
std::cout << "Library version: " << clf.getVersion() << std::endl;
tie(X, y, features, className, states) = loadDataset(file_name, true);
torch::Tensor weights = torch::full({ X.size(1) }, 15, torch::kDouble);
@@ -73,7 +73,6 @@ int main(int argc, char* argv[])
oss << "y dimensions: " << y.sizes();
throw std::runtime_error(oss.str());
}
//Classifier& 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, const Smoothing_t smoothing) override;
clf.fit(dataset, features, className, states, weights, bayesnet::Smoothing_t::LAPLACE);
auto score = clf.score(X, y);
std::cout << "File: " << file_name << " Model: BoostAODE score: " << score << std::endl;