org.dmg.pmml.NeuralNetwork Maven / Gradle / Ivy
package org.dmg.pmml;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import javax.xml.bind.annotation.XmlAccessType;
import javax.xml.bind.annotation.XmlAccessorType;
import javax.xml.bind.annotation.XmlAttribute;
import javax.xml.bind.annotation.XmlElement;
import javax.xml.bind.annotation.XmlRootElement;
import javax.xml.bind.annotation.XmlType;
import org.jpmml.schema.Added;
import org.jpmml.schema.Version;
/**
* Java class for anonymous complex type.
*
*
The following schema fragment specifies the expected content contained within this class.
*
*
* <complexType>
* <complexContent>
* <restriction base="{http://www.w3.org/2001/XMLSchema}anyType">
* <sequence>
* <element ref="{http://www.dmg.org/PMML-4_2}Extension" maxOccurs="unbounded" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}MiningSchema"/>
* <element ref="{http://www.dmg.org/PMML-4_2}Output" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}ModelStats" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}ModelExplanation" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}Targets" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}LocalTransformations" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}NeuralInputs"/>
* <element ref="{http://www.dmg.org/PMML-4_2}NeuralLayer" maxOccurs="unbounded"/>
* <element ref="{http://www.dmg.org/PMML-4_2}NeuralOutputs" minOccurs="0"/>
* <element ref="{http://www.dmg.org/PMML-4_2}ModelVerification" minOccurs="0"/>
* </sequence>
* <attribute name="modelName" type="{http://www.w3.org/2001/XMLSchema}string" />
* <attribute name="functionName" use="required" type="{http://www.dmg.org/PMML-4_2}MINING-FUNCTION" />
* <attribute name="algorithmName" type="{http://www.w3.org/2001/XMLSchema}string" />
* <attribute name="activationFunction" use="required" type="{http://www.dmg.org/PMML-4_2}ACTIVATION-FUNCTION" />
* <attribute name="normalizationMethod" type="{http://www.dmg.org/PMML-4_2}NN-NORMALIZATION-METHOD" default="none" />
* <attribute name="threshold" type="{http://www.dmg.org/PMML-4_2}REAL-NUMBER" default="0" />
* <attribute name="width" type="{http://www.dmg.org/PMML-4_2}REAL-NUMBER" />
* <attribute name="altitude" type="{http://www.dmg.org/PMML-4_2}REAL-NUMBER" default="1.0" />
* <attribute name="numberOfLayers" type="{http://www.dmg.org/PMML-4_2}INT-NUMBER" />
* <attribute name="isScorable" type="{http://www.w3.org/2001/XMLSchema}boolean" default="true" />
* </restriction>
* </complexContent>
* </complexType>
*
*
*
*/
@XmlAccessorType(XmlAccessType.FIELD)
@XmlType(name = "", propOrder = {
"extensions",
"miningSchema",
"output",
"modelStats",
"modelExplanation",
"targets",
"localTransformations",
"neuralInputs",
"neuralLayers",
"neuralOutputs",
"modelVerification"
})
@XmlRootElement(name = "NeuralNetwork", namespace = "http://www.dmg.org/PMML-4_2")
public class NeuralNetwork
extends Model
implements HasExtensions
{
@XmlAttribute(name = "modelName")
private String modelName;
@XmlAttribute(name = "functionName", required = true)
private MiningFunctionType functionName;
@XmlAttribute(name = "algorithmName")
private String algorithmName;
@XmlAttribute(name = "activationFunction", required = true)
private ActivationFunctionType activationFunction;
@XmlAttribute(name = "normalizationMethod")
private NnNormalizationMethodType normalizationMethod;
@XmlAttribute(name = "threshold")
private Double threshold;
@XmlAttribute(name = "width")
private Double width;
@XmlAttribute(name = "altitude")
private Double altitude;
@XmlAttribute(name = "numberOfLayers")
private Integer numberOfLayers;
@XmlAttribute(name = "isScorable")
@Added(Version.PMML_4_1)
private Boolean scorable;
@XmlElement(name = "Extension", namespace = "http://www.dmg.org/PMML-4_2")
private List extensions;
@XmlElement(name = "MiningSchema", namespace = "http://www.dmg.org/PMML-4_2", required = true)
private MiningSchema miningSchema;
@XmlElement(name = "Output", namespace = "http://www.dmg.org/PMML-4_2")
private Output output;
@XmlElement(name = "ModelStats", namespace = "http://www.dmg.org/PMML-4_2")
private ModelStats modelStats;
@XmlElement(name = "ModelExplanation", namespace = "http://www.dmg.org/PMML-4_2")
@Added(Version.PMML_4_0)
private ModelExplanation modelExplanation;
@XmlElement(name = "Targets", namespace = "http://www.dmg.org/PMML-4_2")
private Targets targets;
@XmlElement(name = "LocalTransformations", namespace = "http://www.dmg.org/PMML-4_2")
private LocalTransformations localTransformations;
@XmlElement(name = "NeuralInputs", namespace = "http://www.dmg.org/PMML-4_2", required = true)
private NeuralInputs neuralInputs;
@XmlElement(name = "NeuralLayer", namespace = "http://www.dmg.org/PMML-4_2", required = true)
private List neuralLayers;
@XmlElement(name = "NeuralOutputs", namespace = "http://www.dmg.org/PMML-4_2")
private NeuralOutputs neuralOutputs;
@XmlElement(name = "ModelVerification", namespace = "http://www.dmg.org/PMML-4_2")
private ModelVerification modelVerification;
private final static Double DEFAULT_THRESHOLD = 0.0D;
private final static Double DEFAULT_ALTITUDE = 1.0D;
private final static Boolean DEFAULT_SCORABLE = true;
public NeuralNetwork() {
super();
}
public NeuralNetwork(final MiningFunctionType functionName, final ActivationFunctionType activationFunction, final MiningSchema miningSchema, final NeuralInputs neuralInputs, final List neuralLayers) {
super();
this.functionName = functionName;
this.activationFunction = activationFunction;
this.miningSchema = miningSchema;
this.neuralInputs = neuralInputs;
this.neuralLayers = neuralLayers;
}
/**
* Gets the value of the modelName property.
*
* @return
* possible object is
* {@link String }
*
*/
public String getModelName() {
return modelName;
}
/**
* Sets the value of the modelName property.
*
* @param modelName
* allowed object is
* {@link String }
*
*/
public NeuralNetwork setModelName(String modelName) {
this.modelName = modelName;
return this;
}
/**
* Gets the value of the functionName property.
*
* @return
* possible object is
* {@link MiningFunctionType }
*
*/
public MiningFunctionType getFunctionName() {
return functionName;
}
/**
* Sets the value of the functionName property.
*
* @param functionName
* allowed object is
* {@link MiningFunctionType }
*
*/
public NeuralNetwork setFunctionName(MiningFunctionType functionName) {
this.functionName = functionName;
return this;
}
/**
* Gets the value of the algorithmName property.
*
* @return
* possible object is
* {@link String }
*
*/
public String getAlgorithmName() {
return algorithmName;
}
/**
* Sets the value of the algorithmName property.
*
* @param algorithmName
* allowed object is
* {@link String }
*
*/
public NeuralNetwork setAlgorithmName(String algorithmName) {
this.algorithmName = algorithmName;
return this;
}
/**
* Gets the value of the activationFunction property.
*
* @return
* possible object is
* {@link ActivationFunctionType }
*
*/
public ActivationFunctionType getActivationFunction() {
return activationFunction;
}
/**
* Sets the value of the activationFunction property.
*
* @param activationFunction
* allowed object is
* {@link ActivationFunctionType }
*
*/
public NeuralNetwork setActivationFunction(ActivationFunctionType activationFunction) {
this.activationFunction = activationFunction;
return this;
}
/**
* Gets the value of the normalizationMethod property.
*
* @return
* possible object is
* {@link NnNormalizationMethodType }
*
*/
public NnNormalizationMethodType getNormalizationMethod() {
if (normalizationMethod == null) {
return NnNormalizationMethodType.NONE;
} else {
return normalizationMethod;
}
}
/**
* Sets the value of the normalizationMethod property.
*
* @param normalizationMethod
* allowed object is
* {@link NnNormalizationMethodType }
*
*/
public NeuralNetwork setNormalizationMethod(NnNormalizationMethodType normalizationMethod) {
this.normalizationMethod = normalizationMethod;
return this;
}
/**
* Gets the value of the threshold property.
*
* @return
* possible object is
* {@link Double }
*
*/
public Double getThreshold() {
if (threshold == null) {
return DEFAULT_THRESHOLD;
} else {
return threshold;
}
}
/**
* Sets the value of the threshold property.
*
* @param threshold
* allowed object is
* {@link Double }
*
*/
public NeuralNetwork setThreshold(Double threshold) {
this.threshold = threshold;
return this;
}
/**
* Gets the value of the width property.
*
* @return
* possible object is
* {@link Double }
*
*/
public Double getWidth() {
return width;
}
/**
* Sets the value of the width property.
*
* @param width
* allowed object is
* {@link Double }
*
*/
public NeuralNetwork setWidth(Double width) {
this.width = width;
return this;
}
/**
* Gets the value of the altitude property.
*
* @return
* possible object is
* {@link Double }
*
*/
public Double getAltitude() {
if (altitude == null) {
return DEFAULT_ALTITUDE;
} else {
return altitude;
}
}
/**
* Sets the value of the altitude property.
*
* @param altitude
* allowed object is
* {@link Double }
*
*/
public NeuralNetwork setAltitude(Double altitude) {
this.altitude = altitude;
return this;
}
/**
* Gets the value of the numberOfLayers property.
*
* @return
* possible object is
* {@link Integer }
*
*/
public Integer getNumberOfLayers() {
return numberOfLayers;
}
/**
* Sets the value of the numberOfLayers property.
*
* @param numberOfLayers
* allowed object is
* {@link Integer }
*
*/
public NeuralNetwork setNumberOfLayers(Integer numberOfLayers) {
this.numberOfLayers = numberOfLayers;
return this;
}
/**
* Gets the value of the scorable property.
*
* @return
* possible object is
* {@link Boolean }
*
*/
public boolean isScorable() {
if (scorable == null) {
return DEFAULT_SCORABLE;
} else {
return scorable;
}
}
/**
* Sets the value of the scorable property.
*
* @param scorable
* allowed object is
* {@link Boolean }
*
*/
public NeuralNetwork setScorable(Boolean scorable) {
this.scorable = scorable;
return this;
}
/**
* Gets the value of the extensions property.
*
*
* This accessor method returns a reference to the live list,
* not a snapshot. Therefore any modification you make to the
* returned list will be present inside the JAXB object.
* This is why there is not a set method for the extensions property.
*
*
* For example, to add a new item, do as follows:
*
* getExtensions().add(newItem);
*
*
*
*
* Objects of the following type(s) are allowed in the list
* {@link Extension }
*
*
*/
public List getExtensions() {
if (extensions == null) {
extensions = new ArrayList();
}
return this.extensions;
}
/**
* Gets the value of the miningSchema property.
*
* @return
* possible object is
* {@link MiningSchema }
*
*/
public MiningSchema getMiningSchema() {
return miningSchema;
}
/**
* Sets the value of the miningSchema property.
*
* @param miningSchema
* allowed object is
* {@link MiningSchema }
*
*/
public NeuralNetwork setMiningSchema(MiningSchema miningSchema) {
this.miningSchema = miningSchema;
return this;
}
/**
* Gets the value of the output property.
*
* @return
* possible object is
* {@link Output }
*
*/
public Output getOutput() {
return output;
}
/**
* Sets the value of the output property.
*
* @param output
* allowed object is
* {@link Output }
*
*/
public NeuralNetwork setOutput(Output output) {
this.output = output;
return this;
}
/**
* Gets the value of the modelStats property.
*
* @return
* possible object is
* {@link ModelStats }
*
*/
public ModelStats getModelStats() {
return modelStats;
}
/**
* Sets the value of the modelStats property.
*
* @param modelStats
* allowed object is
* {@link ModelStats }
*
*/
public NeuralNetwork setModelStats(ModelStats modelStats) {
this.modelStats = modelStats;
return this;
}
/**
* Gets the value of the modelExplanation property.
*
* @return
* possible object is
* {@link ModelExplanation }
*
*/
public ModelExplanation getModelExplanation() {
return modelExplanation;
}
/**
* Sets the value of the modelExplanation property.
*
* @param modelExplanation
* allowed object is
* {@link ModelExplanation }
*
*/
public NeuralNetwork setModelExplanation(ModelExplanation modelExplanation) {
this.modelExplanation = modelExplanation;
return this;
}
/**
* Gets the value of the targets property.
*
* @return
* possible object is
* {@link Targets }
*
*/
public Targets getTargets() {
return targets;
}
/**
* Sets the value of the targets property.
*
* @param targets
* allowed object is
* {@link Targets }
*
*/
public NeuralNetwork setTargets(Targets targets) {
this.targets = targets;
return this;
}
/**
* Gets the value of the localTransformations property.
*
* @return
* possible object is
* {@link LocalTransformations }
*
*/
public LocalTransformations getLocalTransformations() {
return localTransformations;
}
/**
* Sets the value of the localTransformations property.
*
* @param localTransformations
* allowed object is
* {@link LocalTransformations }
*
*/
public NeuralNetwork setLocalTransformations(LocalTransformations localTransformations) {
this.localTransformations = localTransformations;
return this;
}
/**
* Gets the value of the neuralInputs property.
*
* @return
* possible object is
* {@link NeuralInputs }
*
*/
public NeuralInputs getNeuralInputs() {
return neuralInputs;
}
/**
* Sets the value of the neuralInputs property.
*
* @param neuralInputs
* allowed object is
* {@link NeuralInputs }
*
*/
public NeuralNetwork setNeuralInputs(NeuralInputs neuralInputs) {
this.neuralInputs = neuralInputs;
return this;
}
/**
* Gets the value of the neuralLayers property.
*
*
* This accessor method returns a reference to the live list,
* not a snapshot. Therefore any modification you make to the
* returned list will be present inside the JAXB object.
* This is why there is not a set method for the neuralLayers property.
*
*
* For example, to add a new item, do as follows:
*
* getNeuralLayers().add(newItem);
*
*
*
*
* Objects of the following type(s) are allowed in the list
* {@link NeuralLayer }
*
*
*/
public List getNeuralLayers() {
if (neuralLayers == null) {
neuralLayers = new ArrayList();
}
return this.neuralLayers;
}
/**
* Gets the value of the neuralOutputs property.
*
* @return
* possible object is
* {@link NeuralOutputs }
*
*/
public NeuralOutputs getNeuralOutputs() {
return neuralOutputs;
}
/**
* Sets the value of the neuralOutputs property.
*
* @param neuralOutputs
* allowed object is
* {@link NeuralOutputs }
*
*/
public NeuralNetwork setNeuralOutputs(NeuralOutputs neuralOutputs) {
this.neuralOutputs = neuralOutputs;
return this;
}
/**
* Gets the value of the modelVerification property.
*
* @return
* possible object is
* {@link ModelVerification }
*
*/
public ModelVerification getModelVerification() {
return modelVerification;
}
/**
* Sets the value of the modelVerification property.
*
* @param modelVerification
* allowed object is
* {@link ModelVerification }
*
*/
public NeuralNetwork setModelVerification(ModelVerification modelVerification) {
this.modelVerification = modelVerification;
return this;
}
public boolean hasExtensions() {
return ((this.extensions!= null)&&(this.extensions.size()> 0));
}
public NeuralNetwork addExtensions(Extension... extensions) {
getExtensions().addAll(Arrays.asList(extensions));
return this;
}
public boolean hasNeuralLayers() {
return ((this.neuralLayers!= null)&&(this.neuralLayers.size()> 0));
}
public NeuralNetwork addNeuralLayers(NeuralLayer... neuralLayers) {
getNeuralLayers().addAll(Arrays.asList(neuralLayers));
return this;
}
@Override
public VisitorAction accept(Visitor visitor) {
VisitorAction status = visitor.visit(this);
if (status == VisitorAction.CONTINUE) {
visitor.pushParent(this);
if ((status == VisitorAction.CONTINUE)&&hasExtensions()) {
status = PMMLObject.traverse(visitor, getExtensions());
}
if (status == VisitorAction.CONTINUE) {
status = PMMLObject.traverse(visitor, getMiningSchema(), getOutput(), getModelStats(), getModelExplanation(), getTargets(), getLocalTransformations(), getNeuralInputs());
}
if ((status == VisitorAction.CONTINUE)&&hasNeuralLayers()) {
status = PMMLObject.traverse(visitor, getNeuralLayers());
}
if (status == VisitorAction.CONTINUE) {
status = PMMLObject.traverse(visitor, getNeuralOutputs(), getModelVerification());
}
visitor.popParent();
}
if (status == VisitorAction.TERMINATE) {
return VisitorAction.TERMINATE;
}
return VisitorAction.CONTINUE;
}
}