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- Pune, India
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 autoencode…
This model generalizes logistic regression to classification problems where the class label y can take on more than two possible values.
In Self-taught learning and Unsupervised feature learning, we will give our algorithms a large amount of unlabeled data with which to learn a good feature representation of the input.
A stacked autoencoder is a neural network consisting of multiple layers of sparse autoencoders in which the outputs of each layer is wired to the inputs of the successive layer.