data_preparation/README.md

data_preparation/

Load and split the .npz data. Used by all training code and notebooks.

prepare_dataset.py: load_all_pooled(), load_per_person() for LOPO, get_numpy_splits() (XGBoost), get_dataloaders() (MLP). Cleans yaw/pitch/roll and EAR to fixed ranges. Face_orientation uses 10 features: head_deviation, s_face, s_eye, h_gaze, pitch, ear_left, ear_avg, ear_right, gaze_offset, perclos.

data_exploration.ipynb: EDA — stats, class balance, histograms, correlations.

You don’t run prepare_dataset directly; import it from models.mlp.train, models.xgboost.train, or the notebooks.