rmontanana/BayesNet
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Remove dataset clone in BoostAODE

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This commit is contained in:
Ricardo Montañana Gómez 2024-03-21 19:35:08 +01:00
parent 58d5a35a35
commit bc0b938cfc
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
2 changed files with 0 additions and 3 deletions
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2
bayesnet/ensembles/BoostAODE.cc
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@ -40,8 +40,6 @@ namespace bayesnet {
if (convergence) { if (convergence) {
// Prepare train & validation sets from train data // Prepare train & validation sets from train data
auto fold = folding::StratifiedKFold(5, y_, 271); auto fold = folding::StratifiedKFold(5, y_, 271);
// save input dataset
dataset_ = torch::clone(dataset);
auto [train, test] = fold.getFold(0); auto [train, test] = fold.getFold(0);
auto train_t = torch::tensor(train); auto train_t = torch::tensor(train);
auto test_t = torch::tensor(test); auto test_t = torch::tensor(test);

1
bayesnet/ensembles/BoostAODE.h
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@ -16,7 +16,6 @@ namespace bayesnet {
void trainModel(const torch::Tensor& weights) override; void trainModel(const torch::Tensor& weights) override;
private: private:
std::vector<int> initializeModels(); std::vector<int> initializeModels();
torch::Tensor dataset_; // Backup the original dataset
torch::Tensor X_train, y_train, X_test, y_test; torch::Tensor X_train, y_train, X_test, y_test;
// Hyperparameters // Hyperparameters
bool bisection = false; // if true, use bisection stratety to add k models at once to the ensemble bool bisection = false; // if true, use bisection stratety to add k models at once to the ensemble