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BernoulliFunction Class |
Inheritance HierarchyAccord.Neuro.ActivationFunctionsBernoulliFunction
Namespace: Accord.Neuro.ActivationFunctions
Assembly: Accord.Neuro (in Accord.Neuro.dll) Version: 3.8.0
Syntax[SerializableAttribute] public class BernoulliFunction : IStochasticFunction, IActivationFunction
The BernoulliFunction type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | BernoulliFunction |
Initializes a new instance of the BernoulliFunction class.
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| BernoulliFunction(Double) |
Initializes a new instance of the BernoulliFunction 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 Bernoulli activation function can be used to create Stochastic Neurons, which can in turn be used to create Deep Belief Networks and Restricted Boltzmann Machines. The use of a Bernoulli function is indicated when the inputs of a problem are discrete, it is, are either 0 or 1. When the inputs are continuous, the use of a GaussianFunction might be more indicated.
As a stochastic activation function, the Bernoulli function is able to generate values following a statistic probability distribution. In this case, the Bernoulli function follows a Bernoulli distribution with its mean given by the output of this class' sigmoidal function.
Examples// Create a Bernoulli function with sigmoid's alpha = 1 BernoulliFunction function = new BernoulliFunction(); // Computes the function output (sigmoid function) double y = function.Function(x: 0.4); // 0.5986876 // Draws a sample from a Bernoulli distribution with // mean given by the function output y (given as before) double z = function.Generate(x: 0.4); // (random, 0 or 1) // Here, z can be either 0 or 1. Since it follows a Bernoulli // distribution with mean 0.59, it is expected to be 1 about // 0.59 of the time. // Now, please note that the above is completely equivalent // to computing the line below (remember, 0.5986876 == y) double w = function.Generate2(y: 0.5986876); // (random, 0 or 1) // We can also compute the derivative of the sigmoid function double d = function.Derivative(x: 0.4); // 0.240260 // Or compute the derivative given the functions' output y double e = function.Derivative2(y: 0.5986876); // 0.240260
See Also