Java: Data Science Made Easy

Backpropagation and neural networks

Backpropagation algorithms are another supervised learning techniques used to train neural networks. As the name suggests, this algorithm calculates the computed output error and then changes the weights of each neuron in a backwards manner. Backpropagation is primarily used with MLP networks. It is important to note forward propagation must occur before backward propagation can be used.

In its most basic form, this algorithm consists of four steps:

1. Perform forward propagation for a given set of inputs.
2. Calculate the error value for each output.
3. Change the weights based upon the calculated error for each node.
4. Perform forward propagation again.

This algorithm completes when the output matches the expected ...