| from traning_zone.traitement_data.feature_engeneering.data_clearning import * | |
| from traning_zone.traitement_data.feature_engeneering.feature_Engineering import * | |
| from traning_zone.modele_zone.modeles import * | |
| from traning_zone.modele_zone.modeles_gridsearch import * | |
| from traning_zone.modele_zone.model import * | |
| import time | |
| import yaml | |
| from dotenv import load_dotenv | |
| import os | |
| load_dotenv() | |
| project_id = os.getenv('PROJECT_ID') | |
| data = pd.read_gbq("SELECT * FROM `c4-group-datagov-dev.classification_refbem.data_big_model`",project_id=project_id) | |
| try : | |
| data.rename(columns={"ITEM_DESC" : "DESCRIPTION"}, inplace=True) | |
| except : | |
| pass | |
| start_time = time.time() | |
| df = clearning_modele(data) | |
| tv_xtrain, tv_xtest, Ytrain, Ytest = engineering_modele(df) | |
| end_time = time.time() | |
| print(f"Temps d'exécution du pré-traitement est : {end_time - start_time} secondes") | |
| for name in modeles.keys(): | |
| try : | |
| start_time = time.time() | |
| trainer_modele(tv_xtrain, Ytrain, tv_xtest, Ytest, modeles[name], name) | |
| end_time = time.time() | |
| print(f"Temps d'exécution du d'apprentissage du modèle {name} est : {end_time - start_time} secondes") | |
| except : | |
| print(f"Erreur lors de l'apprentissage du modèle {name}") |