MultivariateMultiLinearLogisticRegression(IReadOnlyListBoolean, IReadOnlyListIReadOnlyListDouble) Method

Performs a multivariate linear logistic regression on the listed columns.

Definition

Namespace: Meta.Numerics.Statistics
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.2.0+6d77d64445f7d5d91b12e331399c4362ecb25333

C#

public static MultiLinearLogisticRegressionResult MultiLinearLogisticRegression(
	this IReadOnlyList<bool> yColumn,
	IReadOnlyList<IReadOnlyList<double>> xColumns
)

VB

<ExtensionAttribute>
Public Shared Function MultiLinearLogisticRegression ( 
	yColumn As IReadOnlyList(Of Boolean),
	xColumns As IReadOnlyList(Of IReadOnlyList(Of Double))
) As MultiLinearLogisticRegressionResult

C++

public:
[ExtensionAttribute]
static MultiLinearLogisticRegressionResult^ MultiLinearLogisticRegression(
	IReadOnlyList<bool>^ yColumn, 
	IReadOnlyList<IReadOnlyList<double>^>^ xColumns
)

F#

[<ExtensionAttribute>]
static member MultiLinearLogisticRegression : 
        yColumn : IReadOnlyList<bool> * 
        xColumns : IReadOnlyList<IReadOnlyList<float>> -> MultiLinearLogisticRegressionResult

Parameters

yColumn IReadOnlyListBoolean: A column of dependent Boolean variable observations to be predicted.
xColumns IReadOnlyListIReadOnlyListDouble: Columns of independent variable observations that serve as inputs to the regression function.

Return Value

MultiLinearLogisticRegressionResult
A multi-linear fit.

Usage Note

In Visual Basic and C#, you can call this method as an instance method on any object of type IReadOnlyListBoolean. When you use instance method syntax to call this method, omit the first parameter. For more information, see Extension Methods (Visual Basic) or Extension Methods (C# Programming Guide).

Remarks

Note that the xColumns argument is column-oriented, i.e. it is a list of columns, not row-oriented, i.e. a list of rows. Either of these would match the method signature, but only column-oriented inputs will produce correct results.

Exceptions

NullReferenceException	yColumn is , or xColumns is , or one of the x-columns is .
DimensionMismatchException	Not all of the columns contain the same number of observations.
InsufficientDataException	There are too few observations to perform the fit.
DivideByZeroException	The curvature matrix is singular, indicating that the data is independent of one or more of the independent variables, or that two or more variables are linearly dependent.