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MultivariateLinearRegression Methods |
The MultivariateLinearRegression type exposes the following members.
Methods| Name | Description | |
|---|---|---|
 | CoefficientOfDetermination(Double, Double, Double) |
Gets the coefficient of determination, as known as R² (r-squared).
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| CoefficientOfDetermination(Double, Double, Boolean, Double) |
Gets the coefficient of determination, as known as R² (r-squared).
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| Compute(Double) | Obsolete.
Computes the Multiple Linear Regression output for a given input.
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| Compute(Double) | Obsolete.
Computes the Multiple Linear Regression output for a given input.
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| 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.
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| FromData |
Creates a new linear regression directly from data points.
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| GetConfidenceInterval |
Gets the confidence interval for an input point.
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| GetDegreesOfFreedom |
Gets the degrees of freedom when fitting the regression.
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| GetHashCode | Serves as the default hash function. (Inherited from Object.) |
| GetPredictionInterval |
Gets the prediction interval for an input point.
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| GetPredictionStandardError |
Gets the standard error of the prediction for a particular input vector.
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| GetStandardError(Double, Double) |
Gets the overall regression standard error.
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| GetStandardError(Double, Double, Double) |
Gets the standard error of the fit for a particular input vector.
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| GetStandardErrors |
Gets the standard error for each coefficient.
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| 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.
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| 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.
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| 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).) |
Extension Methods| Name | Description | |
|---|---|---|
 | 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.) |
| To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
| ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
See Also