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Radial Basis Function Network - What is the difference between MLP network and radial basis function network?
Answer
In terms of architecture, radial basis function (RBF) networks normally contain three layers: an input layer, a hidden layer with radial basis function neurons, and an output layer; multi-layer perceptrons (MLPs) have two or more intermediate layers.
Other useful AI terms
- What are the advantages of radial basis function neural network?
- What is RBF network for pattern classification?
- What is a radial basis function network?
- What is radial basis function neural network R?
- What is the difference between MLP network and radial basis function network?
- Are radial basis function networks supervised or unsupervised?
AI suggestions
- What are the advantages of radial basis function neural network?
- What is RBF network for pattern classification?
- What is a radial basis function network?
- What is radial basis function neural network R?
- What is the difference between MLP network and radial basis function network?
- Are radial basis function networks supervised or unsupervised?