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