IEmClusterAnalysisSettings

Assembly: Modeller;

Namespace: Prognoz.Platform.Interop.Modeller;

Description

The IEmClusterAnalysisSettings interface determines Hierarchic Cluster Analysis method calculation parameters.

Inheritance hierarchy

          IEmMethodSettings

          IEmClusterAnalysisSettings

Comments

Hierarchical cluster analysis is a method of dividing a set of multidimensional objects into homogenous groups. This is an agglomerative method. Agglomerative methods consistently combine separate objects into clusters.

To create an object with calculation parameters use the IExpressModeller.CreateClusterAnalysisSettings method.

Properties

  Property name Brief description
ClusterCount The ClusterCount property determines the number of clusters, into which object set must be divided.
ClusterLink The ClusterLink property determines the type of links between clusters.
ClusterObjects The ClusterObjects property returns hierarchic cluster analysis objects collection.
DendogramOrientation The DendogramOrientation property determines the orientation of a dendogram.
ObjectDistance The ObjectDistance property determines metric type used in the calculations.
Standartization The Standartization property determines indicators standardization method.
StdValues The StdValues property determines standardization coefficients values.

Properties inherited from IEmMethodSettings

  Property name Brief description
Format The Format property determines a set of sections displayed in the report of express modeling method calculation.
MissingData The MissingData property returns missing initial data processing parameters, used by the express modeling method.
Period The Period property returns calculation period parameters for the express modeling method.
ReportSettings The ReportSettings property returns report parameters for calculating the express modeling method.
Sections The Sections property returns report sections data of express modeling method calculation.

See also:

Modeller Assembly Interfaces | Hierarchical cluster analysis