traning_zone/modele_zone/modeles.py

from traning_zone.data_import.data_importation import *
import pandas as pd
import numpy as np
import os

import warnings
warnings.filterwarnings("ignore")

import joblib
#Import metrics
from sklearn.metrics import balanced_accuracy_score
from sklearn.metrics import classification_report ,  confusion_matrix, accuracy_score, mean_absolute_error

import json

def trainer(X_train, Y_train, X_test, Y_test, Model, name,classe):

    try :
        os.mkdir(f'traning_zone/mini_modèles/{classe}')
        try : 
            os.mkdir(f'traning_zone/mini_modèles/{classe}/{name}')
        except FileExistsError:
             pass 
    except FileExistsError:
        try : 
            os.mkdir(f'traning_zone/mini_modèles/{classe}/{name}')
        except FileExistsError:
            pass
    
    classifier = Model.fit(X_train,Y_train)

    joblib.dump(classifier, open(f"traning_zone/mini_modèles/{classe}/{name}/{name}.pkl", 'wb'))
    Y_pred = classifier.predict(X_test)

    score = balanced_accuracy_score(Y_test, Y_pred)

    with open(f"traning_zone/mini_modèles/{classe}/{name}/balanced_accuracy_score_score.json", "w") as jsonfile:
        json.dump(score, jsonfile)
    
    scores = classification_report(Y_test, Y_pred)

    with open(f"traning_zone/mini_modèles/{classe}/{name}/classification_report_score.json", "w") as jsonfil:
        json.dump(scores, jsonfil)

    print(f'le modèle {name} est terminé')
    return 



def trainer_modele(X_train, Y_train, X_test, Y_test, Model, name):

    try :
        os.mkdir(f'traning_zone/modèles')
        try : 
            os.mkdir(f'traning_zone/modèles/{name}')
        except FileExistsError:
             pass 
    except FileExistsError:
        try : 
            os.mkdir(f'traning_zone/modèles/{name}')
        except FileExistsError:
            pass
    
    classifier = Model.fit(X_train,Y_train)

    joblib.dump(classifier, open(f"traning_zone/modèles/{name}/{name}.pkl", 'wb'))
    Y_pred = classifier.predict(X_test)

    score = balanced_accuracy_score(Y_test, Y_pred)

    with open(f"traning_zone/modèles/{name}/balanced_accuracy_score_score.json", "w") as jsonfile:
        json.dump(score, jsonfile)
    
    scores = classification_report(Y_test, Y_pred)

    with open(f"traning_zone/modèles/{name}/classification_report_score.json", "w") as jsonfil:
        json.dump(scores, jsonfil)

    print(f'le modèle {name} est terminé')
    return