Can you make a confusion matrix? This is the case where it shines
you mean this right? ```py pd.DataFrame( confusion_matrix(y_true, y_pred, labels=['Dropout', 'Enrolled', 'Graduate']), index=['Dropout', 'Enrolled', 'Graduate'], columns=['Dropout', 'Enrolled', 'Graduate'] ) # original data -----SVC----- precision recall f1-score support Dropout 0.83 0.68 0.75 284 Enrolled 0.40 0.58 0.47 159 Graduate 0.83 0.79 0.81 442 accuracy 0.71 885 macro avg 0.68 0.68 0.67 885 weighted avg 0.75 0.71 0.73 885 Dropout Enrolled Graduate Dropout 193 57 34 Enrolled 28 92 39 Graduate 12 83 347 # after down sample -----SVC----- precision recall f1-score support Dropout 0.78 0.67 0.72 200 Enrolled 0.62 0.66 0.64 199 Graduate 0.75 0.81 0.78 200 accuracy 0.71 599 macro avg 0.72 0.71 0.71 599 weighted avg 0.72 0.71 0.71 599 Dropout Enrolled Graduate Dropout 134 50 16 Enrolled 30 131 38 Graduate 7 30 163 ```