BasePrincipalComponentAnalysis Class

Base class for Principal Component Analyses (PCA and KPCA).

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningTransformBaseDouble, Double
    Accord.MachineLearningMultipleTransformBaseDouble, Double
      Accord.Statistics.Analysis.BaseBasePrincipalComponentAnalysis
        Accord.Statistics.AnalysisKernelPrincipalComponentAnalysis
        Accord.Statistics.AnalysisPrincipalComponentAnalysis

Namespace: Accord.Statistics.Analysis.Base
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public abstract class BasePrincipalComponentAnalysis : MultipleTransformBase<double[], double>

<SerializableAttribute>
Public MustInherit Class BasePrincipalComponentAnalysis
	Inherits MultipleTransformBase(Of Double(), Double)

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The BasePrincipalComponentAnalysis type exposes the following members.

Constructors

	Name	Description
	BasePrincipalComponentAnalysis	Initializes a new instance of the BasePrincipalComponentAnalysis class.

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Properties

	Name	Description
	ComponentMatrix	Obsolete. Gets a matrix whose columns contain the principal components. Also known as the Eigenvectors or loadings matrix.
	ComponentProportions	The respective role each component plays in the data set.
	Components	Gets the Principal Components in a object-oriented structure.
	ComponentVectors	Gets a matrix whose columns contain the principal components. Also known as the Eigenvectors or loadings matrix.
	CumulativeProportions	The cumulative distribution of the components proportion role. Also known as the cumulative energy of the principal components.
	Eigenvalues	Provides access to the Eigenvalues stored during the analysis.
	ExplainedVariance	Gets or sets the amount of explained variance that should be generated by this model. This value will alter the NumberOfOutputs that can be generated by this model.
	MaximumNumberOfOutputs	Gets the maximum number of outputs (dimensionality of the output vectors) that can be generated by this model.
	Means	Gets the column mean of the source data given at method construction.
	Method	Gets or sets the method used by this analysis.
	NumberOfInputs	Gets the number of inputs accepted by the model. (Inherited from TransformBaseTInput, TOutput.)
	NumberOfOutputs	Gets or sets the number of outputs (dimensionality of the output vectors) that should be generated by this model.
	Overwrite	Gets or sets whether calculations will be performed overwriting data in the original source matrix, using less memory.
	Result	Obsolete. Gets the resulting projection of the source data given on the creation of the analysis into the space spawned by principal components.
	SingularValues	Provides access to the Singular Values stored during the analysis. If a covariance method is chosen, then it will contain an empty vector.
	Source	Obsolete. Returns the original data supplied to the analysis.
	StandardDeviations	Gets the column standard deviations of the source data given at method construction.
	Token	Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.
	Whiten	Gets or sets whether the transformation result should be whitened (have unit standard deviation) before it is returned.

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Methods

	Name	Description
	CreateComponents	Creates additional information about principal components.
	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.)
	GetNumberOfComponents	Returns the minimal number of principal components required to represent a given percentile of the data.
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	Transform(TInput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Inherited from MultipleTransformBaseTInput, TOutput.)
	Transform(Double)	Obsolete. Obsolete.
	Transform(Double)	Applies the transformation to an input, producing an associated output. (Overrides MultipleTransformBaseTInput, TOutputTransform(TInput).)
	Transform(TInput, TOutput)	Applies the transformation to an input, producing an associated output. (Inherited from MultipleTransformBaseTInput, TOutput.)
	Transform(Double, Int32)	Obsolete. Projects a given matrix into principal component space.
	Transform(Double, Double)	Applies the transformation to an input, producing an associated output. (Overrides MultipleTransformBaseTInput, TOutputTransform(TInput, TOutput).)
	Transform(Double, Int32)	Obsolete. Projects a given matrix into principal component space.
	Transform(Double, Int32)	Obsolete. Projects a given matrix into principal component space.

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Fields

	Name	Description
	array	Obsolete
	covarianceMatrix	Obsolete
	onlyCovarianceMatrixAvailable	Obsolete
	result	Obsolete
	saveResult	Obsolete
	source	Obsolete

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Extension Methods

	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.)

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Reference

Accord.Statistics.Analysis.Base Namespace