RegularizedRegressionModel Methods

Methods

Compute() Computes the model.
(Inherited from Model)
Obsolete.
Compute(ParallelOptions) Computes the model.
(Inherited from Model)
Obsolete.
Contains Returns whether another RegressionModel<T> is nested within this instance.
(Inherited from RegressionModel<T>)
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
FinalizeAllows 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.
(Overrides Model.FitCore(ModelInput, ParallelOptions))
GetAkaikeInformationCriterion Returns the Akaike information criterion (AIC) value for the model.
(Inherited from RegressionModel<T>)
GetBayesianInformationCriterion Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from RegressionModel<T>)
GetDurbinWatsonStatistic Gets the Durbin-Watson statistic for the residuals of the regression.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetNormalityOfResidualsTest() Returns a test to verify that the residuals follow a normal distribution.
GetNormalityOfResidualsTest(TestOfNormality) Returns a test to verify that the residuals follow a normal distribution.
GetRegularizationPath Returns a matrix whose rows contain the parameter values of the model using the corresponding value in the supplied vector of regularization parameters.
GetRegularizationPathParameters() Constructs a vector of suitable regularization parameter values based on the model's data.
GetRegularizationPathParameters(Int32) Constructs a range of suitable regularization parameter values based on the model's data.
GetRegularizationPathParameters(Int32, Double) Constructs a range of suitable regularization parameter values based on the model's data.
GetTypeGets the Type of the current instance.
(Inherited from Object)
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Predict(IDataFrame, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
Predict(Matrix<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
Predict(Vector<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
PredictCore(Matrix<T>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Inherited from RegressionModel<T>)
PredictCore(Vector<T>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Inherited from RegressionModel<T>)
ResetComputation Clears all fitted model parameters.
(Inherited from Model)
Obsolete.
ResetFit Clears all fitted 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 RegressionModel<T>)
ToStringReturns a string that represents the current object.
(Inherited from Model)

See Also