Late Fusion

Late fusion combines per-view predictions (for example, one prediction vector per modality) into a final output. This module includes weighted majority voting. The reusable base class lives in polyview.base.

class polyview.fusion.late.MajorityVote(*args: Any, **kwargs: Any)

Bases: BaseLateFusion

Fuse per-view discrete predictions with sample-wise majority vote.

Parameters:

• weights (sequence of float or None, default=None) – Optional non-negative per-view weights. If None, each view gets weight 1.0. Must have one value per view.

• tie_break ({"first", "random"}, default="first") – Strategy used when multiple classes receive the same max vote. - “first”: choose the smallest class label among tied classes. - “random”: choose a random tied class (reproducible via random_state).

• random_state (int or None, default=None) – Seed used only when tie_break='random'.

fit(preds_by_view: List[Iterable], y=None) → MajorityVote

fit_predict(preds_by_view: List[Iterable], y=None) → numpy.ndarray

predict(preds_by_view: List[Iterable]) → numpy.ndarray