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• Extreme.DataAnalysis.Models
  • ClassificationModel(T) Class
  • ClusteringModel(T) Class
  • ITransformationModel Interface
  • Model Class
  • ModelExtensions Class
  • ModelFitOptions Class
  • ModelInput Class
  • ModelInputCategory Enumeration
  • ModelInputFormat Enumeration
  • ModelInputGroup Class
  • ModelSerialization Enumeration
  • ModelStatus Enumeration
  • ModelTerm Class
  • ModelTermCollection Class
  • ModelTermKind Enumeration
  • RegressionModel(T) Class
  • TransformationModel(T) Class
• RegressionModel(T) Class
  • RegressionModel(T) Constructor
  • Properties
  • Methods
• Properties
  • AdjustedRSquared Property
  • AnovaTable Property
  • CovarianceMatrix Property
  • DegreesOfFreedom Property
  • DependentVariable Property
  • FStatistic Property
  • IndependentVariables Property
  • LogLikelihood Property
  • Parameters Property
  • ParameterValues Property
  • Predictions Property
  • PValue Property
  • Residuals Property
  • ResidualSumOfSquares Property
  • RSquared Property
  • StandardError Property

RegressionModelT Properties

Extreme Optimization Numerical Libraries for .NET Professional

The RegressionModelT generic type exposes the following members.

Properties

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	Name	Description
	AdjustedRSquared	Gets the adjusted R Squared value for the regression.
	AnovaTable	Gets the AnovaTable that summarizes the results of this model.
	BaseFeatureIndex	Gets an index containing the keys of the columns that are required inputs to the model. (Inherited from Model.)
	Computed	Obsolete. Gets whether the model has been computed. (Inherited from Model.)
	CovarianceMatrix	Gets the covariance matrix of the model parameters.
	Data	Gets an object that contains all the data used as input to the model. (Inherited from Model.)
	DegreesOfFreedom	Gets the total degrees of freedom of the data.
	DependentVariable	Gets a vector that contains the dependent variable that is to be fitted.
	Fitted	Gets whether the model has been computed. (Inherited from Model.)
	FStatistic	Gets the F statistic for the regression.
	IndependentVariables	Gets a matrix whose columns contain the independent variables in the model.
	InputSchema	Gets the schema for the features used for fitting the model. (Inherited from Model.)
	LogLikelihood	Gets the log-likelihood that the model generated the data.
	MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance. (Inherited from Model.)
	ModelSchema	Gets the collection of variables used in the model. (Inherited from Model.)
	NumberOfObservations	Gets the number of observations the model is based on. (Inherited from Model.)
	ParallelOptions	Gets or sets an object that specifies how the calculation of the model should be parallelized. (Inherited from Model.)
	Parameters	Gets the collection of parameters associated with this model.
	ParameterValues	Gets the values of the parameters associated with this model.
	Predictions	Gets a vector containing the model's predicted values for the dependent variable.
	PValue	Gets the probability corresponding to the F statistic for the regression.
	Residuals	Gets a vector containing the residuals of the model.
	ResidualSumOfSquares	Gets the sum of squares of the residuals of the model.
	RSquared	Gets the R Squared value for the regression.
	StandardError	Gets the standard error of the regression.
	Status	Gets the status of the model, which determines which information is available. (Inherited from Model.)
	SupportsWeights	Indicates whether the model supports case weights. (Inherited from Model.)
	Weights	Gets or sets the actual weights. (Inherited from Model.)

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See Also

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Reference

RegressionModelT Class

Extreme.DataAnalysis.Models Namespace

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