LinearDiscriminantAnalysis Constructor

Definition

Namespace: Numerics.NET.Statistics.Multivariate
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2

Overload List

LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[])	Constructs a new LinearDiscriminantAnalysis.
LinearDiscriminantAnalysis(IDataFrame, String)	Constructs a new LinearDiscriminantAnalysis.
LinearDiscriminantAnalysis(ModelInput, Vector<Double>[])	Constructs a fitted linear discriminant analysis model.
LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[], Vector<Double>)	Constructs a new LinearDiscriminantAnalysis.
LinearDiscriminantAnalysis(IDataFrame, String, String[])	Constructs a new LinearDiscriminantAnalysis.
LinearDiscriminantAnalysis(Vector<Double>, Matrix<Double>, Vector<Double>)	Constructs a new SimpleRegressionModel.

LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[])

Constructs a new LinearDiscriminantAnalysis.

public LinearDiscriminantAnalysis(
	ICategoricalVector dependentVariable,
	params Vector<double>[] independentVariables
)

Visual Basic

Public Sub New ( 
	dependentVariable As ICategoricalVector,
	ParamArray independentVariables As Vector(Of Double)()
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	ICategoricalVector^ dependentVariable, 
	... array<Vector<double>^>^ independentVariables
)

new : 
        dependentVariable : ICategoricalVector * 
        independentVariables : Vector<float>[] -> LinearDiscriminantAnalysis

Parameters

dependentVariable ICategoricalVector: A categorical vector that specifies the dependent variable.
independentVariables Vector<Double>[]: An array of vectors that contain the independent variables.

Exceptions

ArgumentNullException

dependentVariable is null.

-or-

independentVariables is null.

LinearDiscriminantAnalysis(IDataFrame, String)

Constructs a new LinearDiscriminantAnalysis.

public LinearDiscriminantAnalysis(
	IDataFrame dataFrame,
	string formula
)

Visual Basic

Public Sub New ( 
	dataFrame As IDataFrame,
	formula As String
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	IDataFrame^ dataFrame, 
	String^ formula
)

new : 
        dataFrame : IDataFrame * 
        formula : string -> LinearDiscriminantAnalysis

Parameters

dataFrame IDataFrame: A data frame containing the data for the regression.
formula String: A formula that specifies the variables in the model.

Exceptions

FormatException

The formula is not in the correct format.

LinearDiscriminantAnalysis(ModelInput, Vector<Double>[])

Constructs a fitted linear discriminant analysis model.

public LinearDiscriminantAnalysis(
	ModelInput specification,
	Vector<double>[] coefficients
)

Visual Basic

Public Sub New ( 
	specification As ModelInput,
	coefficients As Vector(Of Double)()
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	ModelInput^ specification, 
	array<Vector<double>^>^ coefficients
)

new : 
        specification : ModelInput * 
        coefficients : Vector<float>[] -> LinearDiscriminantAnalysis

Parameters

specification ModelInput
coefficients Vector<Double>[]

Remarks

Models created with this constructor do not carry any information about the source data or the fit results.

LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[], Vector<Double>)

Constructs a new LinearDiscriminantAnalysis.

public LinearDiscriminantAnalysis(
	ICategoricalVector dependentVariable,
	Vector<double>[] independentVariables,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentVariable As ICategoricalVector,
	independentVariables As Vector(Of Double)(),
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	ICategoricalVector^ dependentVariable, 
	array<Vector<double>^>^ independentVariables, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentVariable : ICategoricalVector * 
        independentVariables : Vector<float>[] * 
        ?weights : Vector<float> 
(* Defaults:
        let _weights = defaultArg weights null
*)
-> LinearDiscriminantAnalysis

Parameters

dependentVariable ICategoricalVector: A vector that specifies the dependent variable.
independentVariables Vector<Double>[]: An array of vectors that contain the independent variables.
weights Vector<Double> (Optional): Optional. A vector containing the case weights.

Exceptions

ArgumentNullException

dependentVariable is null.

-or-

independentVariables is null.

LinearDiscriminantAnalysis(IDataFrame, String, String[])

Constructs a new LinearDiscriminantAnalysis.

public LinearDiscriminantAnalysis(
	IDataFrame dataFrame,
	string dependentVariable,
	params string[] independentVariables
)

Visual Basic

Public Sub New ( 
	dataFrame As IDataFrame,
	dependentVariable As String,
	ParamArray independentVariables As String()
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	IDataFrame^ dataFrame, 
	String^ dependentVariable, 
	... array<String^>^ independentVariables
)

new : 
        dataFrame : IDataFrame * 
        dependentVariable : string * 
        independentVariables : string[] -> LinearDiscriminantAnalysis

Parameters

dataFrame IDataFrame: A data frame containing the data for the regression.
dependentVariable String: The name of the dependent variable.
independentVariables String[]: An array containing the names of the independent variable.

LinearDiscriminantAnalysis(Vector<Double>, Matrix<Double>, Vector<Double>)

Constructs a new SimpleRegressionModel.

public LinearDiscriminantAnalysis(
	Vector<double> dependentData,
	Matrix<double> independentData,
	Vector<double>? weights = null
)

Visual Basic

Public Sub New ( 
	dependentData As Vector(Of Double),
	independentData As Matrix(Of Double),
	Optional weights As Vector(Of Double) = Nothing
)

C++/CLI

public:
LinearDiscriminantAnalysis(
	Vector<double>^ dependentData, 
	Matrix<double>^ independentData, 
	Vector<double>^ weights = nullptr
)

new : 
        dependentData : Vector<float> * 
        independentData : Matrix<float> * 
        ?weights : Vector<float> 
(* Defaults:
        let _weights = defaultArg weights null
*)
-> LinearDiscriminantAnalysis

Parameters

dependentData Vector<Double>: A vector that contains the data for the dependent variable.
independentData Matrix<Double>: A matrix that contains the data for the independent variable.
weights Vector<Double> (Optional): A vector containing the weights.

Remarks

The columns

Exceptions

ArgumentNullException

dependentData is null.

-or-

independentData is null.

LinearDiscriminantAnalysis Constructor

Definition

Overload List

LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[])

Parameters

Exceptions

LinearDiscriminantAnalysis(IDataFrame, String)

Parameters

Exceptions

LinearDiscriminantAnalysis(ModelInput, Vector<Double>[])

Parameters

Remarks

LinearDiscriminantAnalysis(ICategoricalVector, Vector<Double>[], Vector<Double>)

Parameters

Exceptions

LinearDiscriminantAnalysis(IDataFrame, String, String[])

Parameters

LinearDiscriminantAnalysis(Vector<Double>, Matrix<Double>, Vector<Double>)

Parameters

Remarks

Exceptions

See Also

Reference