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BaseSupportVectorClassificationTModel, TKernel, TInput Class |
Namespace: Accord.MachineLearning.VectorMachines.Learning
public abstract class BaseSupportVectorClassification<TModel, TKernel, TInput> : BinaryLearningBase<TModel, TInput>, ISupportVectorMachineLearning<TInput>, ISupervisedBinaryLearning<ISupportVectorMachine<TInput>, TInput>, ISupervisedMulticlassLearning<ISupportVectorMachine<TInput>, TInput>, ISupervisedMultilabelLearning<ISupportVectorMachine<TInput>, TInput>, ISupervisedLearning<ISupportVectorMachine<TInput>, TInput, int[]>, ISupervisedLearning<ISupportVectorMachine<TInput>, TInput, bool[]>, ISupervisedLearning<ISupportVectorMachine<TInput>, TInput, int>, ISupervisedLearning<ISupportVectorMachine<TInput>, TInput, bool>, ISupervisedLearning<ISupportVectorMachine<TInput>, TInput, double> where TModel : Object, ISupportVectorMachine<TInput> where TKernel : Object, IKernel<TInput>
The BaseSupportVectorClassificationTModel, TKernel, TInput type exposes the following members.
Name | Description | |
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![]() | BaseSupportVectorClassificationTModel, TKernel, TInput |
Initializes a new instance of the BaseSupportVectorClassificationTModel, TKernel, TInput class.
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![]() | BaseSupportVectorClassificationTModel, TKernel, TInput(ISupportVectorMachineTInput, TInput, Int32) |
Obsolete.
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Name | Description | |
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![]() | C |
Gets or sets the cost values associated with each input vector.
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![]() | Complexity |
Complexity (cost) parameter C. Increasing the value of C forces the creation
of a more accurate model that may not generalize well. If this value is not
set and UseComplexityHeuristic is set to true, the framework
will automatically guess a value for C. If this value is manually set to
something else, then UseComplexityHeuristic will be automatically
disabled and the given value will be used instead.
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![]() | Inputs |
Gets or sets the input vectors for training.
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![]() | Kernel |
Gets or sets the kernel function use to create a
kernel Support Vector Machine. If this property
is set, UseKernelEstimation will be
set to false.
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![]() | Model |
Gets or sets the classifier being learned.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | NegativeWeight |
Gets or sets the negative class weight. This should be a
value higher than 0 indicating how much of the Complexity
parameter C should be applied to instances carrying the negative label.
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![]() | Outputs |
Gets or sets the output labels for each training vector.
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![]() | PositiveWeight |
Gets or sets the positive class weight. This should be a
value higher than 0 indicating how much of the Complexity
parameter C should be applied to instances carrying the positive label.
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![]() | Token |
Gets or sets a cancellation token that can be used to
stop the learning algorithm while it is running.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | UseClassProportions |
Gets or sets a value indicating whether the weight ratio to be used between
Complexity values for negative and positive instances should
be computed automatically from the data proportions. Default is false.
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![]() | UseComplexityHeuristic |
Gets or sets a value indicating whether the Complexity parameter C
should be computed automatically by employing an heuristic rule.
Default is true.
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![]() | UseKernelEstimation |
Gets or sets whether initial values for some kernel parameters
should be estimated from the data, if possible. Default is true.
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![]() | WeightRatio |
Gets or sets the weight ratio between positive and negative class
weights. This ratio controls how much of the Complexity
parameter C should be applied to the positive class.
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Name | Description | |
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![]() | ComputeError | Obsolete.
Computes the error rate for a given set of input and outputs.
|
![]() | 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.
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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.) |
![]() | GetHashCode | Serves as the default hash function. (Inherited from Object.) |
![]() | GetType | Gets the Type of the current instance. (Inherited from Object.) |
![]() | InnerRun |
Runs the main body of the learning algorithm.
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![]() | Learn(TInput, Boolean, Double) |
Learns a model that can map the given inputs to the given outputs.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | Learn(TInput, Double, Double) |
Learns a model that can map the given inputs to the given outputs.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | Learn(TInput, Int32, Double) |
Learns a model that can map the given inputs to the given outputs.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | Learn(TInput, Int32, Double) |
Learns a model that can map the given inputs to the given outputs.
(Inherited from BinaryLearningBaseTModel, TInput.) |
![]() | Learn(TInput, Boolean, Double) |
Learns a model that can map the given inputs to the given outputs.
(Overrides BinaryLearningBaseTModel, TInputLearn(TInput, Boolean, Double).) |
![]() | MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
![]() | Run | Obsolete.
Obsolete.
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![]() | Run(Boolean) | Obsolete.
Obsolete.
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![]() | ToString | Returns a string that represents the current object. (Inherited from Object.) |
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.) |