Feedforward neural network
A feedforward neural network is an artificial neural network where connections between the units do not form a cycle. This is different from recurrent neural networks.
The feedforward neural network was the first and simplest type of artificial neural network devised. In this network, the information moves in only one direction, forward, from the input nodes, through the hidden nodes (if any) and to the output nodes. There are no cycles or loops in the network.
Feedforward Connection은 Concrete Strength처럼 전방향으로만 레이어간에 연결이 되어진 모델의 뉴럴 네트워크입니다.
Feature
- 가장 단순한 형태의 첫번째 뉴럴 네트워크
- Cycle 또는 loop가 없는 형태
- recurrent neural network와는 다름
- 실무에서 쓰일수 있는 가장 단순한 형태의 뉴럴 네트워크
- Multilayer perceptron 으로도 불림
See also
- Machine learning
- Perceptron
- Neural network
- Feed-forward
- Backpropagation
- Rprop
- The Forward-Forward Algorithm - 딥러닝 선구자 Geoffrey Hinton, 새로운 딥러닝 알고리듬 "FF"