error backpropagation
Error backpropagation is a process used in artificial neural networks to calculate and adjust the weights of the connections between neurons. It involves propagating the error incurred in the output layer back through the network, layer by layer, in order to determine how much each connection contributed to the overall error. This allows for the iterative refinement of the network's weights and improves its accuracy in making predictions or performing tasks.
Requires login.
Related Concepts (1)
Similar Concepts
- backpropagation through time
- backpropagation through time (bptt)
- backward pass
- error calculation
- error estimation
- error handling
- error in reasoning
- error propagation
- error reduction
- error signal
- error-based learning
- inference and forward propagation
- inference errors
- multilayer perceptrons
- truncation error