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KernelDiscriminantAnalysis Properties

The KernelDiscriminantAnalysis type exposes the following members.

Properties
  NameDescription
Protected propertyClassCount
Gets the observation count for each class.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyClasses
Gets information about the distinct classes in the analyzed data.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyClassifications Obsolete.
Gets the original classifications (labels) of the source data given on the moment of creation of this analysis object.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyClassifier
Protected propertyClassMeans
Gets the Mean vector for each class.
(Inherited from BaseDiscriminantAnalysis.)
Protected propertyClassScatter
Gets the Scatter matrix for each class.
(Inherited from BaseDiscriminantAnalysis.)
Protected propertyClassStandardDeviations
Gets the Standard Deviation vector for each class.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyCumulativeProportions
The cumulative distribution of the discriminants factors proportions. Also known as the cumulative energy of the first dimensions of the discriminant space or as the amount of variance explained by those dimensions.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyDiscriminantMatrix Obsolete.
Gets the Eigenvectors obtained during the analysis, composing a basis for the discriminant factor space.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyDiscriminantProportions
Gets the level of importance each discriminant factor has in discriminant space. Also known as amount of variance explained.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyDiscriminants
Gets the discriminant factors in a object-oriented fashion.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyDiscriminantVectors
Gets the Eigenvectors obtained during the analysis, composing a basis for the discriminant factor space.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyEigenvalues
Gets the Eigenvalues found by the analysis associated with each vector of the ComponentMatrix matrix.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyInput
Gets or sets the matrix of original values used to create this analysis. Those values are required to build kernel (Gram) matrices when classifying new samples.
Public propertyKernel
Gets or sets the Kernel used in the analysis.
Public propertyMeans
Gets the mean of the original data given at method construction.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyNumberOfClasses
Gets the number of classes in the analysis.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyNumberOfInputs
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.)
Public propertyNumberOfOutputs
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.)
Public propertyNumberOfSamples
Gets the number of samples used to create the analysis.
(Inherited from BaseDiscriminantAnalysis.)
Protected propertyProjectionMeans
Gets the feature space mean of the projected data.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyRegularization
Gets or sets the regularization parameter to avoid non-singularities at the solution.
Public propertyResult Obsolete.
Gets the resulting projection of the source data given on the creation of the analysis into discriminant space.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyScatterBetweenClass
Gets the Between-Class Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyScatterMatrix
Gets the Total Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyScatterWithinClass
Gets the Within-Class Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.)
Public propertySource Obsolete.
Returns the original supplied data to be analyzed.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyStandardDeviations
Gets the standard mean of the original data given at method construction.
(Inherited from BaseDiscriminantAnalysis.)
Public propertyThreshold
Gets or sets the minimum variance proportion needed to keep a discriminant component. If set to zero, all components will be kept. Default is 0.001 (all components which contribute less than 0.001 to the variance in the data will be discarded).
(Inherited from BaseDiscriminantAnalysis.)
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
(Inherited from BaseDiscriminantAnalysis.)
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