Advanced · Neural Networks
Radial basis function network
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A type of artificial neural network that uses radial basis functions as its activation functions.
Technical Definition
A type of artificial neural network that uses radial basis functions as its activation functions.
How it works
A Radial Basis Function (RBF) network is a feedforward artificial neural network that employs radial basis functions as activation functions. The output of an RBF network is a linear combination of the inputs' radial basis functions, influenced by neuron parameters. These networks are effective for tasks like function approximation, classification, and time series prediction.
Related Concepts
- Activation Function — A non-linear function applied to a neuron's output, enabling the network to learn complex, non-linear relationships.
- Supervised Learning — Learning from input–output pairs where each training example carries a correct label.