Intermediate · Neural Networks
Forget gate
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A component within an LSTM cell that selectively discards information from the cell state to maintain relevant context.
Technical Definition
A component within an LSTM cell that selectively discards information from the cell state to maintain relevant context.
How it works
The forget gate is a crucial part of a Long Short-Term Memory (LSTM) neural network unit. Its function is to decide which pieces of information from the previous cell state should be forgotten or thrown away. This selective forgetting is key to LSTMs' ability to learn long-range dependencies and avoid the vanishing gradient problem.
Related Concepts
- Deep Learning — A subset of machine learning using neural networks with many layers to learn hierarchical representations from large datasets.
- Recurrent Neural Network (RNN) — A neural network with loops that maintain hidden state, designed to process sequential data like text and time series.
- Long Short-Term Memory (LSTM) — An RNN variant with gating mechanisms that can learn long-range dependencies without suffering from vanishing gradients.