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SequentialMinimalOptimization Properties

The SequentialMinimalOptimization type exposes the following members.

Properties
  NameDescription
Public propertyActiveExamples
Gets the indices of the active examples (examples which have the corresponding Lagrange multiplier different than zero).
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyBoundedExamples
Gets the indices of the examples at the boundary (examples which have the corresponding Lagrange multipliers equal to C).
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Protected propertyC
Gets or sets the cost values associated with each input vector.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyCacheSize
Gets or sets the cache size to partially store the kernel matrix. Default is the same number of input vectors, meaning the entire kernel matrix will be computed and cached in memory. If set to zero, the cache will be disabled and all operations will be computed as needed.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyCompact Obsolete.
Gets or sets whether to produce compact models. Compact formulation is currently limited to linear models.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyComplexity
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyEpsilon
Epsilon for round-off errors. Default value is 1e-6.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Protected propertyInputs
Gets or sets the input vectors for training.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyKernel
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyLagrange
Gets the value for the Lagrange multipliers (alpha) for every observation vector.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyModel
Gets or sets the classifier being learned.
(Inherited from BinaryLearningBaseTModel, TInput.)
Public propertyNegativeWeight
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyNonBoundExamples
Gets the indices of the non-bounded examples (examples which have the corresponding Lagrange multipliers between 0 and C).
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Protected propertyOutputs
Gets or sets the output labels for each training vector.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyPositiveWeight
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyShrinking
Gets or sets a value indicating whether shrinking heuristics should be used. Default is false. Note: this property can only be used when Strategy is set to SecondOrder.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyStrategy
Gets or sets the pair selection strategy to be used during optimization.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
(Inherited from BinaryLearningBaseTModel, TInput.)
Public propertyTolerance
Convergence tolerance. Default value is 1e-2.
(Inherited from BaseSequentialMinimalOptimizationTModel, TKernel, TInput.)
Public propertyUseClassProportions
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyUseComplexityHeuristic
Gets or sets a value indicating whether the Complexity parameter C should be computed automatically by employing an heuristic rule. Default is true.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyUseKernelEstimation
Gets or sets whether initial values for some kernel parameters should be estimated from the data, if possible. Default is true.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
Public propertyWeightRatio
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.
(Inherited from BaseSupportVectorClassificationTModel, TKernel, TInput.)
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