﻿ MultivariateLinearRegression Methods

# MultivariateLinearRegression Methods

The MultivariateLinearRegression type exposes the following members.

Methods
NameDescription
CoefficientOfDetermination(Double, Double, Double)
Gets the coefficient of determination, as known as R² (r-squared).
CoefficientOfDetermination(Double, Double, Boolean, Double)
Gets the coefficient of determination, as known as R² (r-squared).
Compute(Double) Obsolete.
Computes the Multiple Linear Regression output for a given input.
Compute(Double) Obsolete.
Computes the Multiple Linear Regression output for a given input.
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.)
FromCoefficients Obsolete.
Creates a new linear regression from the regression coefficients.
FromData
Creates a new linear regression directly from data points.
GetConfidenceInterval
Gets the confidence interval for an input point.
GetDegreesOfFreedom
Gets the degrees of freedom when fitting the regression.
GetHashCode
Serves as the default hash function.
(Inherited from Object.)
GetPredictionInterval
Gets the prediction interval for an input point.
GetPredictionStandardError
Gets the standard error of the prediction for a particular input vector.
GetStandardError(Double, Double)
Gets the overall regression standard error.
GetStandardError(Double, Double, Double)
Gets the standard error of the fit for a particular input vector.
GetStandardErrors
Gets the standard error for each coefficient.
GetType
Gets the Type of the current instance.
(Inherited from Object.)
Inverse
Creates the inverse regression, a regression that can recover the input data given the outputs of this current regression.
MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Regress Obsolete.
Performs the regression using the input vectors and output vectors, returning the sum of squared errors of the fit.
ToString
Returns a string that represents the current object.
(Inherited from Object.)
Transform(TInput)
Applies the transformation to an input, producing an associated output.
(Inherited from MultipleTransformBaseTInput, TOutput.)
Transform(TInput)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from MultipleTransformBaseTInput, TOutput.)
Transform(TInput, TOutput)
Applies the transformation to an input, producing an associated output.
(Inherited from MultipleTransformBaseTInput, TOutput.)
Transform(Double, Double)
Applies the transformation to an input, producing an associated output.
(Overrides MultipleTransformBaseTInput, TOutputTransform(TInput, TOutput).)
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Extension Methods
NameDescription
HasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
IsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)