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GaussianFunction Class |
Inheritance HierarchyAccord.Neuro.ActivationFunctionsGaussianFunction
Namespace: Accord.Neuro.ActivationFunctions
Assembly: Accord.Neuro (in Accord.Neuro.dll) Version: 3.8.0
Syntax[SerializableAttribute] public class GaussianFunction : IStochasticFunction, IActivationFunction
The GaussianFunction type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | GaussianFunction |
Creates a new GaussianFunction.
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| GaussianFunction(Double) |
Creates a new GaussianFunction.
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| GaussianFunction(Double, DoubleRange) |
Initializes a new instance of the GaussianFunction class.
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Properties
Methods| Name | Description | |
|---|---|---|
| Derivative |
Calculates function derivative.
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| Derivative2 |
Calculates function derivative.
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| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
| Function |
Calculates function value.
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| Generate |
Samples a value from the function given a input value.
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| Generate2 |
Samples a value from the function given a function output value.
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| GetHashCode | Serves as the default hash function. (Inherited from Object.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
Extension Methods| Name | Description | |
|---|---|---|
 | HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) |
| IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) |
| To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
| ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
RemarksThe Gaussian activation function can be used to create Stochastic Neurons, which can in turn be used to create Deep Belief Networks and Restricted Boltzmann Machines. In contrast to the BernoulliFunction, the Gaussian can be used to model continuous inputs in Deep Belief Networks. If, however, the inputs of the problem being learned are discrete in nature, the use of a Bernoulli function would be more indicated.
The Gaussian activation function is modeled after a Gaussian (Normal) probability distribution.
This function assumes output variables have been normalized to have zero mean and unit variance.
Examples// Create a Gaussian function with slope alpha = 4.2 GaussianFunction function = new GaussianFunction(4.2); // Computes the function output (linear, y = alpha * x) double y = function.Function(x: 0.2); // 4.2 * 2 = 0.48 // Draws a sample from a Gaussian distribution with // mean given by the function output y (previously 0.48) double z = function.Generate(x: 0.4); // (random, between 0 and 1) // Please note that the above is completely equivalent // to computing the line below (remember, 0.48 == y) double w = function.Generate2(y: 0.48); // (random, between 0 and 1) // We can also compute the derivative of the sigmoid function double d = function.Derivative(x: 0.2); // 4.2 (the slope) // Or compute the derivative given the functions' output y double e = function.Derivative2(y: 0.2); // 4.2 (the slope)
See Also