Represents a statistical model.
SystemObject Extreme.DataAnalysis.ModelsModel Extreme.DataAnalysis.ModelsRegressionModelT Extreme.StatisticsGeneralizedLinearModel Extreme.StatisticsLinearRegressionModel Extreme.StatisticsNonlinearRegressionModel Extreme.StatisticsRegularizedRegressionModel Extreme.StatisticsSimpleRegressionModel
Namespace:
Extreme.DataAnalysis.Models
Assembly:
Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
public abstract class RegressionModel<T> : Model
Public MustInherit Class RegressionModel(Of T)
Inherits Model
generic<typename T>
public ref class RegressionModel abstract : public Model
[<AbstractClassAttribute>]
type RegressionModel<'T> =
class
inherit Model
end
Type Parameters
- T
The RegressionModelT type exposes the following members.
| Name | Description |
---|
 | RegressionModelT |
Constructs a new univariate model based on a model specification.
|
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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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This is an abstract base class and cannot be instantiated directly. Instead, use one of the
inherited types, as listed in the table below:
Note to inheritors: When you inherit from
RegressionModelT,you must override
FitCore(ModelInput, ParallelOptions).
Reference