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import time | |
import numpy as np | |
from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score | |
# fonction d'affichage des performances | |
def performances(y_pred,y_true): | |
r2 = round(r2_score(y_pred,y_true)*100,2) | |
rmse=round(np.sqrt(np.mean(np.power((np.array(y_pred)-y_true),2))),2) | |
return r2, rmse | |
def taken_time(start_time, end_time): | |
return(f"{round((end_time-start_time)/60,2)} min.") |