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  • Extreme.Statistics.Multivariate
    • DendrogramNode Class
    • DistanceMeasures Class
    • Factor Class
    • FactorAnalysis Class
    • FactorCountMethod Enumeration
    • FactorExtractionMethod Enumeration
    • FactorMethod Enumeration
    • FactorRotationMethod Enumeration
    • FactorScoreMethod Enumeration
    • HierarchicalCluster Class
    • HierarchicalClusterAnalysis Class
    • HierarchicalClusterCollection Class
    • KMeansCluster Class
    • KMeansClusterAnalysis Class
    • KMeansInitializationMethod Enumeration
    • LinearDiscriminantAnalysis Class
    • LinearDiscriminantFunction Class
    • LinkageMethod Enumeration
    • PartialLeastSquaresMethod Enumeration
    • PartialLeastSquaresModel Class
    • PrincipalComponent Class
    • PrincipalComponentAnalysis Class
    • PrincipalComponentCollection Class
    • ScalingMethod Enumeration
    • SimilarityMatrix Class

Extreme.Statistics.Multivariate Namespace

Extreme Optimization Numerical Libraries for .NET Professional
The Extreme.Statistics.Multivariate namespace contains classes that implement multivariate statistical analysis techniques.
Classes

  ClassDescription
Public classDendrogramNode
Represents a node in a dendrogram.
Public classDistanceMeasures
Provides access to standard distance measures for hierarchical cluster analysis.
Public classFactor
Represents a factor in a factor analysis.
Public classFactorAnalysis
Represents a Factor Analysis.
Public classHierarchicalCluster
Represents a cluster of cases in a cluster analysis.
Public classHierarchicalClusterAnalysis
Represents a hierarchical cluster analysis of a set of data.
Public classHierarchicalClusterCollection
Represents a collection of clusters.
Public classKMeansCluster
Represents a cluster of cases in a K-means cluster analysis.
Public classKMeansClusterAnalysis
Represents a K-Means cluster analysis.
Public classLinearDiscriminantAnalysis
Represents a linear discriminant classification model.
Public classLinearDiscriminantFunction
Represents a discriminant function.
Public classPartialLeastSquaresModel
Represents a Partial Least Squares (PLS) model.
Public classPrincipalComponent
Represents a component in a PrincipalComponentAnalysis.
Public classPrincipalComponentAnalysis
Represents the Principal Component Analysis (PCA) of a set of data.
Public classPrincipalComponentCollection
Represents a collection of principal components in a PrincipalComponentAnalysis.
Public classSimilarityMatrix
Represents a similarity matrix used in hierarchical clustering.
Enumerations

  EnumerationDescription
Public enumerationFactorCountMethod
Enumerates the possible ways the number of factors in a factor analysis may be determined.
Public enumerationFactorExtractionMethod
Enumarates the possible ways to extract factors in a factor analysis.
Public enumerationFactorMethod
Enumerates the options for performing factor analysis on a correlation or a covariance matrix.
Public enumerationFactorRotationMethod
Enumerates the possible factor rotation methods for a factor analysis.
Public enumerationFactorScoreMethod
Enumerates the ways factor scores may be computed.
Public enumerationKMeansInitializationMethod
Enumerates the methods that may be used to initialize the K-means clustering algorithm.
Public enumerationLinkageMethod
Enumerates the possible linkage methods in hierarchical cluster analysis.
Public enumerationPartialLeastSquaresMethod
Enumerates the algorithms that may be used to compute a partial least squares (PLS) model.
Public enumerationScalingMethod
Enumerates the ways to scale the columns in a Principal Component Analysis.

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