Statements (33)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:convolutional_neural_network
|
| gptkbp:advantage |
fast training
universal approximation capability |
| gptkbp:architecture |
hidden layer
input layer output layer |
| gptkbp:basisFor |
radially symmetric function
|
| gptkbp:centerParameter |
center of radial basis function
|
| gptkbp:commonActivationFunction |
Gaussian function
inverse multiquadric function multiquadric function |
| gptkbp:field |
gptkb:artificial_intelligence
gptkb:machine_learning pattern recognition |
| gptkbp:fullName |
gptkb:Radial_Basis_Function_Network
|
| gptkbp:hiddenLayerActivation |
radial basis function
|
| https://www.w3.org/2000/01/rdf-schema#label |
RBF Network
|
| gptkbp:input |
real-valued vectors
|
| gptkbp:introduced |
Broomhead and Lowe
|
| gptkbp:introducedIn |
1988
|
| gptkbp:limitation |
scalability issues with large datasets
sensitive to choice of centers |
| gptkbp:output |
linear combination of basis functions
|
| gptkbp:relatedTo |
support vector machine
k-means clustering |
| gptkbp:spreadParameter |
width of radial basis function
|
| gptkbp:trainer |
supervised learning for weights
unsupervised learning for centers |
| gptkbp:usedFor |
gptkb:dictionary
function approximation regression |
| gptkbp:bfsParent |
gptkb:Radial_Basis_Function_Network
|
| gptkbp:bfsLayer |
6
|