Implementation of back propagation using neuralnet package



Implementation of back propagation using neuralnet package

The backward propagation of errors or back-propgation  is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent.

The algorithm repeats a two phase cycle propagation and weight update.

When an input vector is presented to the network , it is propgated forward through the network layer by layer.

The goal of back-propgation is to optimize the weights so that the neural network can learn how to correctly map arbitrary inputs to outputs.

Back-propgation is an algorithm for supervised learning of artificial neural networks using gradient descent.

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