Model Class

Represents a statistical model.

Definition

Namespace: Extreme.DataAnalysis.Models
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

public abstract class Model : ISummarizable, 
	IParallelized

Visual Basic

Public MustInherit Class Model
	Implements ISummarizable, IParallelized

C++/CLI

public ref class Model abstract : ISummarizable, 
	IParallelized

[<AbstractClassAttribute>]
type Model = 
    class
        interface ISummarizable
        interface IParallelized
    end

Derived: Extreme.DataAnalysis.Models.ClassificationModel<T>
Extreme.DataAnalysis.Models.ClusteringModel<T>
Extreme.DataAnalysis.Models.RegressionModel<T>
Extreme.DataAnalysis.Models.TransformationModel<T>
Extreme.Statistics.AnovaModel
Extreme.Statistics.Multivariate.PartialLeastSquaresModel
Extreme.Statistics.TimeSeriesAnalysis.TimeSeriesModel<T>
More Less

This is an abstract base class and cannot be instantiated directly. Instead, use one of the inherited types, as listed in the table below:

Class	Description
OneWayAnovaModel	One way between subjects analysis of variance.
OneWayRAnovaModel	One way within subjects analysis of variance
TwoWayAnovaModel	Two way between subjects analysis of variance.
SimpleRegressionModel	A simple linear regression model with one independent variable.
LinearRegressionModel	A multiple linear regression model with multiple independent variables.

Note to inheritors: When you inherit from Model, you must override FitCore(ModelInput, ParallelOptions).

Constructs a new statistical model.

BaseFeatureIndex	Gets an index containing the keys of the columns that are required inputs to the model.
Computed	Gets whether the model has been computed. Obsolete.
Data	Gets an object that contains all the data used as input to the model.
Fitted	Gets whether the model has been computed.
InputSchema	Gets the schema for the features used for fitting the model.
MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance.
ModelSchema	Gets the collection of variables used in the model.
NumberOfObservations	Gets the number of observations the model is based on.
ParallelOptions	Gets or sets an object that specifies how the calculation of the model should be parallelized.
Status	Gets the status of the model, which determines which information is available.
SupportsWeights	Indicates whether the model supports case weights.
Weights	Gets or sets the actual weights.

Compute()	Computes the model. Obsolete.
Compute(ParallelOptions)	Computes the model. Obsolete.
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)
Fit()	Fits the model to the data.
Fit(ParallelOptions)	Fits the model to the data.
FitCore	Computes the model to the specified input using the specified parallelization options.
GetHashCode	Serves as the default hash function. (Inherited from Object)
GetType	Gets the Type of the current instance. (Inherited from Object)
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
ResetComputation	Clears all fitted model parameters. Obsolete.
ResetFit	Clears all fitted model parameters.
SetDataSource	Uses the specified data frame as the source for all input variables.
Summarize()	Returns a string containing a human-readable summary of the object using default options.
Summarize(SummaryOptions)	Returns a string containing a human-readable summary of the object using the specified options.
ToString	Returns a string that represents the current object. (Overrides Object.ToString())

Represents a model with no parameters.