Bases: ABC, Generic[BuffersT, ConfigT, ArrayT]
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fit_epoch(X: ndarray, Y: ndarray, clause_drop_p: float, **kwargs)
Fit one epoch.
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fit_sample(e: int) → float
Fit one sample e.
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get_packed_clauses() → PackedClauses
Return packed clauses.
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get_state_dict() → dict
Get state dictionary for saving the model.
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infer(X: ndarray, force_repack: bool = False) → ndarray
Inference. Calculate class sums for X.
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load_state_dict(state: dict) → None
Written in place, so anything already pointing at these arrays stays valid.
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set_feat_drop(fids: int | list[int], value: int) → None
Set a feature to be ignored.
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transform(X: ndarray, force_repack: bool = False) → ndarray
Calculate clause activations.
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transform_patchwise(X: ndarray, force_repack: bool = False) → ndarray
Patchwise Clause activations.
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wac(X: ndarray, target_classes: ndarray, polarity: int, force_repack: bool = False) → ndarray
Calculate WAC score.
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abstractmethod wic(class_id: int, polarity: int, pw_th: float = 0.0, force_repack: bool = False) → ndarray
Calculate WIC score.