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  • DendrogramNode Class
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  • LinearDiscriminantAnalysis Constructors
  • Properties
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• Methods
  • ComputeModel Method Overloads
  • InverseTransform Method
  • PredictProbabilitiesCore Method Overloads
  • Transform Method

LinearDiscriminantAnalysis Methods

Extreme Optimization Numerical Libraries for .NET Professional

The LinearDiscriminantAnalysis type exposes the following members.

Methods

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	Name	Description
	Compute	Computes the model. (Inherited from Model.)
	Compute(ParallelOptions)	Computes the model. (Inherited from Model.)
	ComputeModel	Computes the model. (Inherited from Model.)
	ComputeModel(ParallelOptions)	Fits the model to the data. (Inherited from Model.)
	ComputeModel(ModelInput, ParallelOptions)	Computes the model using the specified parallelization options. (Overrides ModelComputeModel(ModelInput, ParallelOptions).)
	Contains	Returns whether another ClassificationModel is nested within this instance. (Inherited from ClassificationModel.)
	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.)
	Fit	Fits the model to the data. (Inherited from Model.)
	Fit(ParallelOptions)	Fits the model to the data. (Inherited from Model.)
	FitCore	Computes the model to the specified input using the specified parallelization options. (Inherited from Model.)
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	InverseTransform	Applies the inverse transformation to a set of observations.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Predict(IDataFrame, ModelInputFormat)	Predicts the most likely class based on the specified features. (Inherited from ClassificationModel.)
	Predict(MatrixDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified features. (Inherited from ClassificationModel.)
	Predict(VectorDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified input. (Inherited from ClassificationModel.)
	PredictCore(MatrixDouble, Boolean, Boolean)	Predicts the value of the dependent variable based on the specified values of the features. (Inherited from ClassificationModel.)
	PredictCore(VectorDouble, Boolean, Boolean)	Predicts the class based on the specified values of the features. (Inherited from ClassificationModel.)
	PredictProbabilities(IDataFrame, ModelInputFormat)	Predicts the value of the output corresponding to the specified input. (Inherited from ClassificationModel.)
	PredictProbabilities(MatrixDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified features. (Inherited from ClassificationModel.)
	PredictProbabilities(VectorDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified input. (Inherited from ClassificationModel.)
	PredictProbabilitiesCore(MatrixDouble, MatrixDouble, Boolean, Boolean)	Predicts the probabilities of each class based on the specified values of the features. (Inherited from ClassificationModel.)
	PredictProbabilitiesCore(VectorDouble, VectorDouble, Boolean, Boolean)	Predicts the probabilities of each class based on the specified values of the features. (Overrides ClassificationModelPredictProbabilitiesCore(VectorDouble, VectorDouble, Boolean, Boolean).)
	PredictProbabilitiesInto(IDataFrame, MatrixDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified input. (Inherited from ClassificationModel.)
	PredictProbabilitiesInto(MatrixDouble, MatrixDouble, ModelInputFormat)	Predicts the value of the output corresponding to the specified features. (Inherited from ClassificationModel.)
	PredictProbabilitiesInto(VectorDouble, VectorDouble, ModelInputFormat)	Predicts the probabilities of each class based on the specified features. (Inherited from ClassificationModel.)
	ResetComputation	Clears all computed model parameters. (Inherited from Model.)
	SetDataSource	Uses the specified data frame as the source for all input variables. (Inherited from Model.)
	Summarize	Returns a string containing a human-readable summary of the object using default options. (Inherited from Model.)
	Summarize(SummaryOptions)	Returns a string containing a human-readable summary of the object using the specified options. (Inherited from Model.)
	ToString	Returns a string that represents the current object. (Inherited from Model.)
	Transform	Applies the transformation to a set of observations.

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Extension Methods

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	Name	Description
	Transform(IDataFrame, ModelInputFormat)	Overloaded. Applies the transformation to a set of observations. (Defined by ModelExtensions.)
	Transform(MatrixDouble, ModelInputFormat)	Overloaded. Applies the transformation to a set of observations. (Defined by ModelExtensions.)

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See Also

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Reference

LinearDiscriminantAnalysis Class

Extreme.Statistics.Multivariate Namespace

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