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save at different steps

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Alexis REVELLE 2024-03-28 07:37:10 +00:00
parent 133eb83e84
commit adc62dd056
1 changed files with 5 additions and 0 deletions
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0_5_Machine_Learning.py
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@ -63,6 +63,7 @@ model_result = pd.DataFrame(columns= ["Model", "Accuracy", "Recall", "F1_score",
# Naive Bayes # Naive Bayes
model_result = pipeline_naiveBayes_benchmark(X_train, y_train, X_test, y_test, model_result) model_result = pipeline_naiveBayes_benchmark(X_train, y_train, X_test, y_test, model_result)
save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
print("Naive Bayes : Done") print("Naive Bayes : Done")
# Logistic Regression # Logistic Regression
@ -70,12 +71,16 @@ model_result = pipeline_logreg_benchmark(X_train, y_train, X_test, y_test, model
print("Logistic : Done") print("Logistic : Done")
model_result = pipeline_logreg_cv(X_train, y_train, X_test, y_test, model_result) model_result = pipeline_logreg_cv(X_train, y_train, X_test, y_test, model_result)
save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
print("Logistic CV : Done") print("Logistic CV : Done")
# Random Forest # Random Forest
model_result = pipeline_randomF_benchmark(X_train, y_train, X_test, y_test, model_result) model_result = pipeline_randomF_benchmark(X_train, y_train, X_test, y_test, model_result)
save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
print("Random Forest : Done") print("Random Forest : Done")
model_result = pipeline_randomF_cv(X_train, y_train, X_test, y_test, model_result) model_result = pipeline_randomF_cv(X_train, y_train, X_test, y_test, model_result)
save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
print("Random Forest CV: Done") print("Random Forest CV: Done")
# Save result # Save result