Represents the Principal Component Analysis (PCA) of a set of data.
SystemObject Extreme.StatisticsModel Extreme.StatisticsTransformationModel Extreme.Statistics.MultivariatePrincipalComponentAnalysis
Namespace: Extreme.Statistics.MultivariateAssembly: Extreme.Numerics.Net40 (in Extreme.Numerics.Net40.dll) Version: 6.0.16073.0 (6.0.17058.0)
public sealed class PrincipalComponentAnalysis : TransformationModel
Public NotInheritable Class PrincipalComponentAnalysis
Inherits TransformationModel
public ref class PrincipalComponentAnalysis sealed : public TransformationModel
[<SealedAttribute>]
type PrincipalComponentAnalysis =
class
inherit TransformationModel
end
The PrincipalComponentAnalysis type exposes the following members.
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| Name | Description |
---|
 | BaseFeatureIndex |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model.) |
 | ComponentMatrix |
Gets the matrix whose columns contain the principal components.
|
 | Components |
Returns the collection of principal components.
|
 | Computed |
Gets whether the regression model has been computed.
(Inherited from Model.) |
 | CumulativeVarianceProportions |
Returns the cumulative proportion of the variance that is explained by the components.
|
 | Data |
Gets an object that contains all the data used as input to the model.
(Inherited from Model.) |
 | DependentVariables |
Gets the collection of dependent variables associated with this model.
(Inherited from Model.) |
 | Features |
Gets a matrix that contains the features.
(Inherited from TransformationModel.) |
 | IndependentVariables |
Gets the collection of independent variables associated with this model.
(Inherited from Model.) |
 | InputSchema |
Gets the schema for the features used for fitting the model.
(Inherited from Model.) |
 | MaxDegreeOfParallelism |
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model.) |
 | ModelSchema |
Gets the collection of variables used in the model.
(Inherited from Model.) |
 | NumberOfComponents |
Gets or sets the number of components to retain.
|
 | NumberOfObservations |
Gets the number of observations the model is based on.
(Inherited from MultivariateModel.) |
 | RowCount |
Gets the number of observations.
|
 | ScalingMethod |
Gets or sets the method used to scale the variables.
|
 | ScoreMatrix |
Gets the matrix of component scores.
|
 | Standardize | Obsolete.
Gets or sets whether the variables should be standardized prior to computing the principal components.
|
 | Status |
Gets the status of the model, which determines which information is available.
(Inherited from Model.) |
 | SupportsWeights |
Indicates whether the model supports case weights.
(Inherited from Model.) |
 | VarianceProportions |
Returns the proportion of the variance that is explained by each of the components.
|
 | Weights |
Gets or sets the actual weights.
(Inherited from Model.) |
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Use the PrincipalComponentAnalysis class to obtain information
about the components that contribute the most to the variation in a dataset.
The data for the analysis can be supplied in a variety of formats,
including as a data frame, a DataTable, an array of numerical vectors,
or a matrix.
The Standardize property determines whether each variable should be rescaled to have zero
mean and unit standard deviation. The Compute(ParallelOptions) method performs the actual calculation.
Once the analysis has been completed, the Components property provides access to
a collection of PrincipalComponent objects that provide details about each of the principal components.
The components are sorted in order of their contribution to the variance in the data, in descending order.
The ComponentMatrix property returns the components as the columns of a matrix. The ScoreMatrix
property expresses the observations in terms of the components. The GetPredictions(Int32) method
returns the observations if only the specified number of components is taken into account.
The VarianceProportions and CumulativeVarianceProportions summarize
the contribution of each component. The GetVarianceThreshold(Double) calculates how many components
are needed to explain a certain proportion of the variation.
Numerical Libraries
Supported in: 6.0, 5.x, 4.x
Reference