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OneVsRestLearningTBinary, TModel Class
Base learning algorithm for OneVsRestTModel, TInput multi-class classifiers.
Inheritance Hierarchy
SystemObject
  Accord.MachineLearningParallelLearningBase
    Accord.MachineLearningOneVsRestLearningDouble, TBinary, TModel
      Accord.MachineLearningOneVsRestLearningTBinary, TModel

Namespace:  Accord.MachineLearning
Assembly:  Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0
Syntax
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public abstract class OneVsRestLearning<TBinary, TModel> : OneVsRestLearning<double[], TBinary, TModel>, 
	ISupervisedLearning<TModel, double[], int>
where TBinary : class, Object, IBinaryScoreClassifier<double[]>
where TModel : OneVsRest<TBinary>
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Type Parameters

TBinary
The type for the inner binary classifiers used in the one-vs-rest approach.
TModel
The type of the model being learned.

The OneVsRestLearningTBinary, TModel type exposes the following members.

Constructors
  NameDescription
Protected methodOneVsRestLearningTBinary, TModel
Initializes a new instance of the OneVsRestLearningTBinary, TModel class
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Properties
  NameDescription
Public propertyAggregateExceptions
Gets or sets a value indicating whether the entire training algorithm should stop in case an exception has been detected at just one of the inner binary learning problems. Default is true (execution will not be stopped).
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public propertyIsMultilabel
Gets or sets a value indicating whether the learning algorithm should generate multi-label (as opposed to multi-class) models. If left unspecified, the type of the model will be determined automatically depending on which overload of the Learn(TInput, Boolean, Double) method will be called first by the executing code.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public propertyLearner
Gets or sets a function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public propertyModel
Gets or sets the model being learned.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.)
Public propertyToken
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.)
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Methods
  NameDescription
Public methodConfigureTResult(FuncTResult)
Sets a callback function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy. Calling this method sets the Learner property.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public methodConfigureT, TResult(FuncT, TResult)
Sets a callback function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy. Calling this method sets the Learner property.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Protected methodCreate
Creates an instance of the model to be learned. Inheritors of this abstract class must define this method so new models can be created from the training data.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
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(TInput, Boolean, Double)
Learns a model that can map the given inputs to the given outputs.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public methodLearn(TInput, Int32, Double)
Learns a model that can map the given inputs to the given outputs.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public methodLearn(TInput, Int32, Double)
Learns a model that can map the given inputs to the given outputs.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Protected methodOnSubproblemFinished
Raises the [E:SubproblemFinished] event.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Protected methodOnSubproblemStarted
Raises the [E:SubproblemStarted] event.
(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Events
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