An unsupervised learning algorithm that applies back propagation, setting the target values to be equal to the inputs. Also, we impose a sparsity constraint on the hidden units, then the autoencoder will still discover interesting structure in the data, even if the number of hidden units is large.
An unsupervised learning algorithm that applies back propagation, setting the target values to be equal to the inputs. Also, we impose a sparsity constraint on the hidden units, then the autoencoder will still discover interesting structure in the data, even if the number of hidden units is large.
Refer to following link, http://goo.gl/PAmLG
An unsupervised learning algorithm that applies back propagation, setting the target values to be equal to the inputs. Also, we impose a sparsity constraint on the hidden units, then the autoencoder will still discover interesting structure in the data, even if the number of hidden units is large.