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gptkbp:instance_of
|
gptkb:neural_networks
|
|
gptkbp:analyzes
|
Radial Basis Function Surface
|
|
gptkbp:can_be_combined_with
|
gptkb:neural_networks
gptkb:Recurrent_Neural_Networks
|
|
gptkbp:can_be_used_for
|
Regression Analysis
|
|
gptkbp:developed_by
|
Broomhead and Lowe
|
|
gptkbp:has_activation_function
|
Radial Basis Function
|
|
gptkbp:has_applications_in
|
gptkb:Pattern_Recognition
Control Systems
Signal Processing
|
|
gptkbp:has_layer_type
|
Hidden Layer
Input Layer
Output Layer
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Radial Basis Function Network
|
|
gptkbp:introduced_in
|
gptkb:1988
|
|
gptkbp:is_characterized_by
|
Radial Basis Functions
|
|
gptkbp:is_enhanced_by
|
gptkb:Dropout
L2 Regularization
|
|
gptkbp:is_evaluated_by
|
gptkb:Embedded_Systems
gptkb:cloud_computing
Cross-Validation
Mean Squared Error
Real-Time Systems
|
|
gptkbp:is_implemented_in
|
gptkb:MATLAB
gptkb:Python
gptkb:R
|
|
gptkbp:is_known_for
|
Local Approximation
Universal Approximation Property
|
|
gptkbp:is_optimized_for
|
gptkb:Genetic_Algorithms
gptkb:Docker
Gradient Descent
|
|
gptkbp:is_part_of
|
gptkb:Artificial_Intelligence
gptkb:machine_learning
|
|
gptkbp:is_related_to
|
gptkb:Support_Vector_Machines
Kernel Methods
|
|
gptkbp:is_trained_in
|
Supervised Learning
Unsupervised Learning
|
|
gptkbp:is_used_in
|
Classification
Image Processing
Medical Diagnosis
Time Series Prediction
Financial Forecasting
Function Approximation
|
|
gptkbp:requires
|
Training Data
|
|
gptkbp:sensitivity
|
gptkb:Outliers
|
|
gptkbp:bfsParent
|
gptkb:neural_networks
|
|
gptkbp:bfsLayer
|
4
|