MultilabelSupportVectorLearning Class (original) (raw)

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Note: This API is now obsolete.

Obsolete.

Inheritance Hierarchy

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

Syntax

[ObsoleteAttribute("Please specify the desired kernel function as a template parameter.")] public class MultilabelSupportVectorLearning : BaseMultilabelSupportVectorLearning<double[], SupportVectorMachine<IKernel<double[]>>, IKernel<double[]>, MultilabelSupportVectorMachine>

<ObsoleteAttribute("Please specify the desired kernel function as a template parameter.")> Public Class MultilabelSupportVectorLearning Inherits BaseMultilabelSupportVectorLearning(Of Double(), SupportVectorMachine(Of IKernel(Of Double())), IKernel(Of Double()), MultilabelSupportVectorMachine)

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The MultilabelSupportVectorLearning type exposes the following members.

Constructors

Properties

| | Name | Description | | | -------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Public property | AggregateExceptions | 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 property | Algorithm | Obsolete. Obsolete. | | Public property | IsMultilabel | 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 property | Kernel | Gets or sets the kernel function to be used to learn thekernel support vector machines. | | Public property | Learner | 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 property | Model | Gets or sets the model being learned. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Public property | ParallelOptions | Gets or sets the parallelization options for this algorithm. (Inherited from ParallelLearningBase.) | | Public property | Token | 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

| | Name | Description | | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Public method | ConfigureTResult(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 method | ConfigureT, 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.) | | Public methodStatic member | Convert | Converts SupportVectorMachineLearningConfigurationFunction into a lambda function that can be passed to the Learner property of a MultilabelSupportVectorLearning learning algorithm. | | Protected method | Create | 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. (Overrides OneVsRestLearningTInput, TBinary, TModelCreate(Int32, Int32, Boolean).) | | Public method | Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | | Protected method | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | | Public method | GetHashCode | Serves as the default hash function. (Inherited from Object.) | | Public method | GetType | Gets the Type of the current instance. (Inherited from Object.) | | Public method | Learn(TInput, Boolean, Double) | Learns a model that can map the given inputs to the given outputs. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Public method | Learn(TInput, Int32, Double) | Learns a model that can map the given inputs to the given outputs. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Public method | Learn(TInput, Int32, Double) | Learns a model that can map the given inputs to the given outputs. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Protected method | MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | | Protected method | OnSubproblemFinished | Raises the [E:SubproblemFinished] event. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Protected method | OnSubproblemStarted | Raises the [E:SubproblemStarted] event. (Inherited from OneVsRestLearningTInput, TBinary, TModel.) | | Public method | Run | Obsolete. Obsolete. | | Public method | ToString | Returns a string that represents the current object. (Inherited from Object.) |

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Events

Extension Methods

| | Name | Description | | | ------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Public Extension Method | HasMethod | Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.) | | Public Extension Method | IsEqual | Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices. (Defined by Matrix.) | | Public Extension Method | 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.) | | Public Extension Method | 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.) |

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See Also

Reference