Represents a hierarchical cluster analysis of a set of data.
SystemObject Extreme.DataAnalysis.ModelsModel Extreme.DataAnalysis.ModelsClusteringModelDouble Extreme.Statistics.MultivariateHierarchicalClusterAnalysis
Namespace:
Extreme.Statistics.Multivariate
Assembly:
Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
public class HierarchicalClusterAnalysis : ClusteringModel<double>
Public Class HierarchicalClusterAnalysis
Inherits ClusteringModel(Of Double)
public ref class HierarchicalClusterAnalysis : public ClusteringModel<double>
type HierarchicalClusterAnalysis =
class
inherit ClusteringModel<float>
end
The HierarchicalClusterAnalysis type exposes the following members.
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| Name | Description |
---|
 | 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.) |
 | Data |
Gets an object that contains all the data used as input to the model.
(Inherited from Model.) |
 | DendrogramRoot |
Gets the root node of the dendrogram.
|
 | DistanceMeasure |
Gets or sets the DistanceMeasure used to compute the distance between two cases.
|
 | 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.) |
 | LinkageMethod | |
 | 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.) |
 | SimilarityMatrix |
Gets or sets the similarity matrix.
|
 | Standardize |
Gets or sets whether the variables should be standardized before the clustering is computed.
|
 | 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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Use the HierarchicalClusterAnalysis to identify homogeneous subgroups of cases in a population
using the agglomerative hierarchical clustering method.
The method starts out by treating every case as its own cluster. It then successively combines ("agglomerates")
clusters that are closest to each other until the entire population is one cluster. The order in which clusters
are combined specifies a hierarchy. The last remaining clusters determine membership of the homogeneous groups.
The DistanceMeasure determines how the distance between clusters is calculated.
The default is to use the squared Euclidean distance. The DistanceMeasures class
defines several common distance measures.
The LinkageMethod property determines how cluster distances are updated when two clusters are merged.
The default is the centroid method. The Standardize property determines whether the variables
are transformed to all have the same mean and standard deviation. The default is .
Once the clustering has been computed by calling the Fit method, the
GetClusterPartition(Int32) method can be used to partition the observations.
This method returns a HierarchicalClusterCollection that provides detailed information
about each of the clusters.
The results of a hierarchical cluster analysis are often presented in graphical form as a dendrogram,
a tree-like structure that shows how clusters were combined. The DendrogramRoot property
returns a DendrogramNode object that represents the root of the dendrogram. It provides all
the information necessary to produce a dendrogram. See the DendrogramNode class for details.
Reference