| """Fixed splits, so every router is trained and scored on the same rows.""" | |
| import pandas as pd | |
| from sklearn.model_selection import train_test_split | |
| from .paths import PATIENT_COMMENTS | |
| SEED = 24679 | |
| def public_split() -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]: | |
| """Patient Comments as (train, val, held_out): about 76.5% / 8.5% / 15%, stratified by label. | |
| val picks the best epoch when fine-tuning; held_out is only ever scored. | |
| """ | |
| comments = pd.read_csv(PATIENT_COMMENTS) | |
| rest, held_out = train_test_split(comments, test_size=0.15, stratify=comments["label"], random_state=SEED) | |
| train, val = train_test_split(rest, test_size=0.10, stratify=rest["label"], random_state=SEED) | |
| return train, val, held_out | |