ClusteringModel<T> Class

Serves as the base class for classes that build clustering models.

Definition

Namespace: Numerics.NET.DataAnalysis.Models
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4

public abstract class ClusteringModel<T> : Model

Visual Basic

Public MustInherit Class ClusteringModel(Of T)
	Inherits Model

C++/CLI

generic<typename T>
public ref class ClusteringModel abstract : public Model

[<AbstractClassAttribute>]
type ClusteringModel<'T> = 
    class
        inherit Model
    end

Derived: Numerics.NET.Statistics.Multivariate.HierarchicalClusterAnalysis
Numerics.NET.Statistics.Multivariate.KMeansClusterAnalysis

Use the ClusteringModel<T> class as the base class for classes that create clustering or unsupervised learning models.

ClusteringModel<T>(Matrix<T>)	Constructs a new ClusteringModel<T>.
ClusteringModel<T>(IDataFrame, String)	Constructs a new ClusteringModel<T>.
ClusteringModel<T>(IDataFrame, String[])	Constructs a new ClusteringModel<T>.
ClusteringModel<T>(IEnumerable<Vector<Double>>, Vector<Double>)	Constructs a new ClusteringModel<T>.

BaseFeatureIndex	Gets an index containing the keys of the columns that are required inputs to the model. (Inherited from Model)
Computed	Gets whether the model has been computed. (Inherited from Model) Obsolete.
Data	Gets an object that contains all the data used as input to the model. (Inherited from Model)
Fitted	Gets whether the model has been computed. (Inherited from Model)
InputSchema	Gets the schema for the features used for fitting the model. (Inherited from Model)
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)
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)

Compute()	Computes the model. (Inherited from Model) Obsolete.
Compute(ParallelOptions)	Computes the model. (Inherited from 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. (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. (Inherited from Model)
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. (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 Model)
ToString	Returns a string that represents the current object. (Inherited from Model)