ezyrb.reduction.ae.AE.fit

AE.fit(values)

Build the AE given ‘values’ and perform training.

Training procedure information:

• optimizer: Adam’s method with default parameters (see, e.g., https://pytorch.org/docs/stable/optim.html);

• loss: self.loss (if none, the Mean Squared Loss is set by default).

• stopping criterion: the fulfillment of the requested tolerance on the training loss compatibly with the prescribed budget of training iterations (if type(self.stop_training) is list); if type(self.stop_training) is int or type(self.stop_training) is float, only the number of maximum iterations or the accuracy level on the training loss is considered as the stopping rule, respectively.

Parameters:

values (numpy.ndarray) – the (training) values in the points.