(cls, items)
| 141 | |
| 142 | @classmethod |
| 143 | def cb_multi_fi(cls, items): |
| 144 | preds, golds = zip(*items) |
| 145 | preds = np.array(preds) |
| 146 | golds = np.array(golds) |
| 147 | f11 = sklearn.metrics.f1_score(y_true=golds == 0, y_pred=preds == 0) |
| 148 | f12 = sklearn.metrics.f1_score(y_true=golds == 1, y_pred=preds == 1) |
| 149 | f13 = sklearn.metrics.f1_score(y_true=golds == 2, y_pred=preds == 2) |
| 150 | avg_f1 = mean([f11, f12, f13]) |
| 151 | return avg_f1 |
| 152 | |
| 153 | def aggregation(self): |
| 154 | return { |