BackPropagationAutoencoder bae = TrainerFactory.backPropagationAutoencoder(ae, trainInputProvider, testInputProvider, error, new NNRandomInitializer(new MersenneTwisterRandomInitializer(-0.01f, 0.01f)), 0.02f, 0.7f, 0f, 0f, 0f, 1, 1, 100);
// log data to console
bae.addEventListener(new LogTrainingListener(Thread.currentThread().getStackTrace()[1].getMethodName()));
bae.train();
// the output layer is needed only during the training phase...
ae.removeLayer(ae.getOutputLayer());
bae.test();