Package org.dmg.pmml.bayesian_network

Class ObjectFactory

java.lang.Object

org.dmg.pmml.bayesian_network.ObjectFactory

public class ObjectFactory
extends java.lang.Object

This object contains factory methods for each Java content interface and Java element interface generated in the org.dmg.pmml.bayesian_network package.

An ObjectFactory allows you to programmatically construct new instances of the Java representation for XML content. The Java representation of XML content can consist of schema derived interfaces and classes representing the binding of schema type definitions, element declarations and model groups. Factory methods for each of these are provided in this class.

Constructor Summary

Constructors

Constructor	Description
ObjectFactory()	Create a new ObjectFactory that can be used to create new instances of schema derived classes for package: org.dmg.pmml.bayesian_network

Method Summary

Modifier and Type	Method	Description
BayesianNetworkModel	createBayesianNetworkModel()	Create an instance of BayesianNetworkModel
BayesianNetworkNodes	createBayesianNetworkNodes()	Create an instance of BayesianNetworkNodes
ContinuousConditionalProbability	createContinuousConditionalProbability()	Create an instance of ContinuousConditionalProbability
ContinuousDistribution	createContinuousDistribution()	Create an instance of ContinuousDistribution
ContinuousNode	createContinuousNode()	Create an instance of ContinuousNode
DiscreteConditionalProbability	createDiscreteConditionalProbability()	Create an instance of DiscreteConditionalProbability
DiscreteNode	createDiscreteNode()	Create an instance of DiscreteNode
LognormalDistribution	createLognormalDistribution()	Create an instance of LognormalDistribution
Lower	createLower()	Create an instance of Lower
Mean	createMean()	Create an instance of Mean
NormalDistribution	createNormalDistribution()	Create an instance of NormalDistribution
ParentValue	createParentValue()	Create an instance of ParentValue
TriangularDistribution	createTriangularDistribution()	Create an instance of TriangularDistribution
UniformDistribution	createUniformDistribution()	Create an instance of UniformDistribution
Upper	createUpper()	Create an instance of Upper
ValueProbability	createValueProbability()	Create an instance of ValueProbability
Variance	createVariance()	Create an instance of Variance

Methods inherited from class java.lang.Object

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

Constructor Detail

ObjectFactory

public ObjectFactory()

Create a new ObjectFactory that can be used to create new instances of schema derived classes for package: org.dmg.pmml.bayesian_network

Method Detail

createBayesianNetworkModel

public BayesianNetworkModel createBayesianNetworkModel()

Create an instance of BayesianNetworkModel

Returns:

the new instance of BayesianNetworkModel

createBayesianNetworkNodes

public BayesianNetworkNodes createBayesianNetworkNodes()

Create an instance of BayesianNetworkNodes

Returns:

the new instance of BayesianNetworkNodes

createDiscreteNode

public DiscreteNode createDiscreteNode()

Create an instance of DiscreteNode

Returns:

the new instance of DiscreteNode

createDiscreteConditionalProbability

public DiscreteConditionalProbability createDiscreteConditionalProbability()

Create an instance of DiscreteConditionalProbability

Returns:

the new instance of DiscreteConditionalProbability

createParentValue

public ParentValue createParentValue()

Create an instance of ParentValue

Returns:

the new instance of ParentValue

createValueProbability

public ValueProbability createValueProbability()

Create an instance of ValueProbability

Returns:

the new instance of ValueProbability

createContinuousNode

public ContinuousNode createContinuousNode()

Create an instance of ContinuousNode

Returns:

the new instance of ContinuousNode

createContinuousConditionalProbability

public ContinuousConditionalProbability createContinuousConditionalProbability()

Create an instance of ContinuousConditionalProbability

Returns:

the new instance of ContinuousConditionalProbability

createContinuousDistribution

public ContinuousDistribution createContinuousDistribution()

Create an instance of ContinuousDistribution

Returns:

the new instance of ContinuousDistribution

createTriangularDistribution

public TriangularDistribution createTriangularDistribution()

Create an instance of TriangularDistribution

Returns:

the new instance of TriangularDistribution

createMean

public Mean createMean()

Create an instance of Mean

Returns:

the new instance of Mean

createLower

public Lower createLower()

Create an instance of Lower

Returns:

the new instance of Lower

createUpper

public Upper createUpper()

Create an instance of Upper

Returns:

the new instance of Upper

createNormalDistribution

public NormalDistribution createNormalDistribution()

Create an instance of NormalDistribution

Returns:

the new instance of NormalDistribution

createVariance

public Variance createVariance()

Create an instance of Variance

Returns:

the new instance of Variance

createLognormalDistribution

public LognormalDistribution createLognormalDistribution()

Create an instance of LognormalDistribution

Returns:

the new instance of LognormalDistribution

createUniformDistribution

public UniformDistribution createUniformDistribution()

Create an instance of UniformDistribution

Returns:

the new instance of UniformDistribution