Hi, at the last step where the accuracy is printed for the Fast Regularized Ensembles of models (frem) as follows:
print('F1 scoreswith FREM') for category in categories: print(category, '\t\t {:.2f}'.format(np.mean(decoder.cv_scores_[category])))
Shouldn't it be averaged using frem scores instead of the ones from the decoder model? Hence, it would be:
print('F1 scoreswith FREM') for category in categories: print(category, '\t\t {:.2f}'.format(np.mean(frem.cv_scores_[category])))
Hi, at the last step where the accuracy is printed for the Fast Regularized Ensembles of models (frem) as follows:
print('F1 scoreswith FREM') for category in categories: print(category, '\t\t {:.2f}'.format(np.mean(decoder.cv_scores_[category])))Shouldn't it be averaged using frem scores instead of the ones from the decoder model? Hence, it would be:
print('F1 scoreswith FREM') for category in categories: print(category, '\t\t {:.2f}'.format(np.mean(frem.cv_scores_[category])))