Module datarush.analytics

Package com.pervasive.datarush.analytics.cluster

Class PMMLClusteringModel

java.lang.Object

com.pervasive.datarush.analytics.pmml.PMMLModel

com.pervasive.datarush.analytics.cluster.PMMLClusteringModel

public final class PMMLClusteringModel
extends PMMLModel

PMML clustering model. This model uses the standard PMML Clustering model.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	PMMLClusteringModel.Builder	Builder for PMMLClusteringModel instances.

Nested classes/interfaces inherited from class com.pervasive.datarush.analytics.pmml.PMMLModel

PMMLModel.MiningFunction

Constructor Summary

Constructors

Constructor	Description
PMMLClusteringModel(Document document)	Create a PMMLClusteringModel out of an PMML document

Method Summary

Modifier and Type	Method	Description
static PMMLClusteringModel.Builder	builder(PMMLModelSpec spec, ModelClass modelClass, ComparisonMeasure comparisonMeasure, Cluster[] clusters)	Creates a builder that builds PMMLClusteringModel instances with the provided model specification, model class, comparison measure and clusters.
protected void	buildModelElement(Element element)	Subclasses must implement this method to fill-in the contents of the model element.
String	getAlgorithmName()	Gets the name of the algorithm used to create this model
ClusteringField[]	getClusteringFields()	Gets the ClusteringFields of this model.
Cluster[]	getClusters()	Gets the Clusters of this model.
ComparisonMeasure	getComparisonMeasure()	Gets the ComparisonMeasure of this model.
MissingValueWeights	getMissingValueWeights()	Gets the MissingValueWeights of this model.
ModelClass	getModelClass()	Get the ModelClass of this model.
protected String	getModelElementName()	Return the element name of the primary model element associated with this PMML
String	getModelName()	Gets the name of this model.
boolean	isScorable()	Gets whether this model is scorable.
protected void	parseModelElement(Element element)	Parse the given model element into the respective model object.

Methods inherited from class com.pervasive.datarush.analytics.pmml.PMMLModel

findModelElement, getAnnotationText, getModelExplanation, getModelSpec, getVersion, parse, setAnnotationText, setModelExplanation, setVersion, toPMML

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PMMLClusteringModel

public PMMLClusteringModel(Document document)

Create a PMMLClusteringModel out of an PMML document

Parameters:

document - the document containing the PMML model

Method Detail

getModelName

public String getModelName()

Gets the name of this model.

Returns:

the name of this model

getAlgorithmName

public String getAlgorithmName()

Gets the name of the algorithm used to create this model

Returns:

the name of the algorithm used to create this model

getModelClass

public ModelClass getModelClass()

Get the ModelClass of this model.

Returns:

the ModelClass of this model

isScorable

public boolean isScorable()

Gets whether this model is scorable.

Returns:

true, if the model is scorable, false otherwise

getClusteringFields

public ClusteringField[] getClusteringFields()

Gets the ClusteringFields of this model.

Returns:

the ClusteringFields of this model

getMissingValueWeights

public MissingValueWeights getMissingValueWeights()

Gets the MissingValueWeights of this model.

Returns:

the MissingValueWeights of this model

getClusters

public Cluster[] getClusters()

Gets the Clusters of this model.

Returns:

the Clusters of this model

getComparisonMeasure

public ComparisonMeasure getComparisonMeasure()

Gets the ComparisonMeasure of this model.

Returns:

the ComparisonMeasure of this model

buildModelElement

protected void buildModelElement(Element element)

Description copied from class: PMMLModel

Subclasses must implement this method to fill-in the contents of the model element. At the time this method is invoked, the element will have its name and MiningSchema sub-element populated.

Specified by:

buildModelElement in class PMMLModel

Parameters:

element - the model element

getModelElementName

protected String getModelElementName()

Description copied from class: PMMLModel

Return the element name of the primary model element associated with this PMML

Specified by:

getModelElementName in class PMMLModel

Returns:

the element name of the primary model element

parseModelElement

protected void parseModelElement(Element element)

Description copied from class: PMMLModel

Parse the given model element into the respective model object.

Specified by:

parseModelElement in class PMMLModel

Parameters:

element - root element of model object

builder

public static PMMLClusteringModel.Builder builder(PMMLModelSpec spec,
                                                  ModelClass modelClass,
                                                  ComparisonMeasure comparisonMeasure,
                                                  Cluster[] clusters)

Creates a builder that builds PMMLClusteringModel instances with the provided model specification, model class, comparison measure and clusters. For other parameters defaults, will be used: the model will be scorable, have no name or algorithm name, no clustering fields, and its missing value weights element will have an empty weights array.

Parameters:

spec - the PMMLModelSpec

modelClass - the ModelClass

comparisonMeasure - the ComparisonMeasure

clusters - the Clusters

Returns:

PMMLClusteringModel.Builder