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  • Extreme.Statistics.Multivariate
    • DendrogramNode Class
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    • PartialLeastSquaresModel Class
    • PrincipalComponent Class
    • PrincipalComponentAnalysis Class
    • PrincipalComponentCollection Class
    • ScalingMethod Enumeration
    • SimilarityMatrix Class
  • LinearDiscriminantAnalysis Class
    • LinearDiscriminantAnalysis Constructors
    • Properties
    • Methods
  • Methods
    • FitCore Method
    • InverseTransform Method
    • PredictProbabilitiesCore Method Overloads
    • Summarize Method Overloads
    • Transform Method

LinearDiscriminantAnalysis Methods

Extreme Optimization Numerical Libraries for .NET Professional

The LinearDiscriminantAnalysis type exposes the following members.

Methods

  NameDescription
Public methodCompute Obsolete.
Computes the model.
(Inherited from Model.)
Public methodCompute(ParallelOptions) Obsolete.
Computes the model.
(Inherited from Model.)
Public methodContains
Returns whether another ClassificationModelT is nested within this instance.
(Inherited from ClassificationModelT.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodFit
Fits the model to the data.
(Inherited from Model.)
Public methodFit(ParallelOptions)
Fits the model to the data.
(Inherited from Model.)
Protected methodFitCore
Computes the model to the specified input using the specified parallelization options.
(Overrides ModelFitCore(ModelInput, ParallelOptions).)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodInverseTransform
Applies the inverse transformation to a set of observations.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodPredict(IDataFrame, ModelInputFormat)
Predicts the most likely class based on the specified features.
(Inherited from ClassificationModelT.)
Public methodPredict(MatrixT, ModelInputFormat)
Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModelT.)
Public methodPredict(VectorT, ModelInputFormat)
Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModelT.)
Protected methodPredictCore(MatrixT, Boolean)
Predicts the value of the dependent variable based on the specified values of the features.
(Inherited from ClassificationModelT.)
Protected methodPredictCore(VectorT, Boolean)
Predicts the class based on the specified values of the features.
(Inherited from ClassificationModelT.)
Public methodPredictProbabilities(IDataFrame, ModelInputFormat)
Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModelT.)
Public methodPredictProbabilities(MatrixT, ModelInputFormat)
Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModelT.)
Public methodPredictProbabilities(VectorT, ModelInputFormat)
Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModelT.)
Protected methodPredictProbabilitiesCore(MatrixT, MatrixDouble, Boolean)
Predicts the probabilities of each class based on the specified values of the features.
(Inherited from ClassificationModelT.)
Protected methodPredictProbabilitiesCore(VectorDouble, VectorDouble, Boolean)
Predicts the probabilities of each class based on the specified values of the features.
(Overrides ClassificationModelTPredictProbabilitiesCore(VectorT, VectorDouble, Boolean).)
Public methodPredictProbabilitiesInto(IDataFrame, MatrixDouble, ModelInputFormat)
Predicts the value of the output corresponding to the specified input.
(Inherited from ClassificationModelT.)
Public methodPredictProbabilitiesInto(MatrixT, MatrixDouble, ModelInputFormat)
Predicts the value of the output corresponding to the specified features.
(Inherited from ClassificationModelT.)
Public methodPredictProbabilitiesInto(VectorT, VectorDouble, ModelInputFormat)
Predicts the probabilities of each class based on the specified features.
(Inherited from ClassificationModelT.)
Public methodResetComputation Obsolete.
Clears all fitted model parameters.
(Inherited from Model.)
Public methodResetFit
Clears all fitted model parameters.
(Inherited from Model.)
Public methodSetDataSource
Uses the specified data frame as the source for all input variables.
(Inherited from Model.)
Public methodSummarize
Returns a string containing a human-readable summary of the object using default options.
(Inherited from Model.)
Public methodSummarize(SummaryOptions)
Returns a string containing a human-readable summary of the object using the specified options.
(Overrides ModelSummarize(SummaryOptions).)
Public methodToString
Returns a string that represents the current object.
(Inherited from Model.)
Public methodTransform
Applies the transformation to a set of observations.
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Extension Methods

  NameDescription
Public Extension MethodTransform(IDataFrame, ModelInputFormat)Overloaded.
Applies the transformation to a set of observations.
(Defined by ModelExtensions.)
Public Extension MethodTransform(MatrixDouble, ModelInputFormat)Overloaded.
Applies the transformation to a set of observations.
(Defined by ModelExtensions.)
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See Also

Reference

LinearDiscriminantAnalysis Class
Extreme.Statistics.Multivariate Namespace

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