PerceptronLearning Class

Perceptron learning algorithm.

Inheritance Hierarchy

SystemObject
Accord.Neuro.LearningPerceptronLearning

Namespace: Accord.Neuro.Learning
Assembly: Accord.Neuro (in Accord.Neuro.dll) Version: 3.8.0

Syntax

public class PerceptronLearning : ISupervisedLearning

Public Class PerceptronLearning
	Implements ISupervisedLearning

The PerceptronLearning type exposes the following members.

Constructors

	Name	Description
	PerceptronLearning	Initializes a new instance of the PerceptronLearning class.

Properties

	Name	Description
	LearningRate	Learning rate, [0, 1].

Methods

	Name	Description
	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.)
	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.)
	Run	Runs learning iteration.
	RunEpoch	Runs learning epoch.
	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.)

Remarks

This learning algorithm is used to train one layer neural network of Activation Neurons with the Threshold activation function.

See information about Perceptron and its learning algorithm.