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MultinomialLogisticLearningTMethod Class
Gradient optimization for Multinomial logistic regression fitting.
Inheritance Hierarchy
SystemObject
  Accord.Statistics.Models.Regression.FittingMultinomialLogisticLearningTMethod

Namespace:  Accord.Statistics.Models.Regression.Fitting
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
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public class MultinomialLogisticLearning<TMethod> : ISupervisedLearning<MultinomialLogisticRegression, double[], int>, 
	ISupervisedLearning<MultinomialLogisticRegression, double[], int[]>, ISupervisedLearning<MultinomialLogisticRegression, double[], double[]>, 
	ISupervisedLearning<MultinomialLogisticRegression, double[], bool[]>
where TMethod : new(), Object, IFunctionOptimizationMethod<double[], double>
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Type Parameters

TMethod

The MultinomialLogisticLearningTMethod type exposes the following members.

Constructors
  NameDescription
Public methodMultinomialLogisticLearningTMethod
Creates a new MultinomialLogisticLearningTMethod.
Public methodMultinomialLogisticLearningTMethod(MultinomialLogisticRegression)
Creates a new MultinomialLogisticLearningTMethod.
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Properties
  NameDescription
Public propertyMethod
Gets or sets the optimization method used to optimize the parameters (learn) the MultinomialLogisticRegression.
Public propertyMiniBatchSize
Gets or sets the number of samples to be used as the mini-batch. If set to 0 (or a negative number) the total number of training samples will be used as the mini-batch.
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodLearn(Double, Boolean, Double)
Learns a model that can map the given inputs to the given outputs.
Public methodLearn(Double, Double, Double)
Learns a model that can map the given inputs to the given outputs.
Public methodLearn(Double, Int32, Double)
Learns a model that can map the given inputs to the given outputs.
Public methodLearn(Double, Int32, Double)
Learns a model that can map the given inputs to the given outputs.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(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.)
Public Extension MethodToTOverloaded.
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.)
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See Also