dataeval.detectors.ood.OOD_AE¶

class dataeval.detectors.ood.OOD_AE(model, device=None)¶

Autoencoder based out-of-distribution detector.

Parameters:¶

model : Autoencoder¶

An Autoencoder model.

device : str | torch.device | None¶

fit(x_ref, threshold_perc, loss_fn=None, optimizer=None, epochs=20, batch_size=64, verbose=False)¶

Train the model and infer the threshold value.

Parameters:¶

x_ref : ArrayLike¶

Training data.

threshold_perc : float, default 100.0¶

Percentage of reference data that is normal.

loss_fn : Callable | None, default None¶

Loss function used for training.

optimizer : Optimizer, default keras.optimizers.Adam¶

Optimizer used for training.

epochs : int, default 20¶

Number of training epochs.

batch_size : int, default 64¶

Batch size used for training.

verbose : bool, default True¶

Whether to print training progress.

Return type:¶

None