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org.dmg.pmml.regression.RegressionModel Maven / Gradle / Ivy
package org.dmg.pmml.regression;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import javax.xml.bind.annotation.XmlAttribute;
import javax.xml.bind.annotation.XmlElement;
import javax.xml.bind.annotation.XmlEnum;
import javax.xml.bind.annotation.XmlEnumValue;
import javax.xml.bind.annotation.XmlRootElement;
import javax.xml.bind.annotation.XmlType;
import javax.xml.bind.annotation.adapters.XmlJavaTypeAdapter;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonPropertyOrder;
import com.fasterxml.jackson.annotation.JsonRootName;
import org.dmg.pmml.Extension;
import org.dmg.pmml.FieldName;
import org.dmg.pmml.HasExtensions;
import org.dmg.pmml.LocalTransformations;
import org.dmg.pmml.MathContext;
import org.dmg.pmml.MiningFunction;
import org.dmg.pmml.MiningSchema;
import org.dmg.pmml.Model;
import org.dmg.pmml.ModelExplanation;
import org.dmg.pmml.ModelStats;
import org.dmg.pmml.ModelVerification;
import org.dmg.pmml.Output;
import org.dmg.pmml.PMMLObject;
import org.dmg.pmml.StringValue;
import org.dmg.pmml.Targets;
import org.dmg.pmml.Visitor;
import org.dmg.pmml.VisitorAction;
import org.dmg.pmml.adapters.FieldNameAdapter;
import org.jpmml.model.annotations.ValueConstructor;
@XmlRootElement(name = "RegressionModel", namespace = "http://www.dmg.org/PMML-4_4")
@XmlType(name = "", propOrder = {
"extensions",
"miningSchema",
"output",
"modelStats",
"modelExplanation",
"targets",
"localTransformations",
"regressionTables",
"modelVerification"
})
@JsonRootName("RegressionModel")
@JsonPropertyOrder({
"modelName",
"miningFunction",
"algorithmName",
"modelType",
"targetField",
"normalizationMethod",
"scorable",
"mathContext",
"extensions",
"miningSchema",
"output",
"modelStats",
"modelExplanation",
"targets",
"localTransformations",
"regressionTables",
"modelVerification"
})
public class RegressionModel
extends Model
implements HasExtensions
{
@XmlAttribute(name = "modelName")
@JsonProperty("modelName")
private String modelName;
@XmlAttribute(name = "functionName", required = true)
@JsonProperty("functionName")
private MiningFunction miningFunction;
@XmlAttribute(name = "algorithmName")
@JsonProperty("algorithmName")
private String algorithmName;
@XmlAttribute(name = "modelType")
@org.jpmml.model.annotations.Deprecated((org.dmg.pmml.Version.PMML_3_0))
@JsonProperty("modelType")
private RegressionModel.ModelType modelType;
@XmlAttribute(name = "targetFieldName")
@XmlJavaTypeAdapter(FieldNameAdapter.class)
@org.jpmml.model.annotations.Deprecated((org.dmg.pmml.Version.PMML_3_0))
@JsonProperty("targetFieldName")
private FieldName targetField;
@XmlAttribute(name = "normalizationMethod")
@JsonProperty("normalizationMethod")
private RegressionModel.NormalizationMethod normalizationMethod;
@XmlAttribute(name = "isScorable")
@org.jpmml.model.annotations.Added((org.dmg.pmml.Version.PMML_4_1))
@JsonProperty("isScorable")
private Boolean scorable;
@XmlAttribute(name = "x-mathContext")
@org.jpmml.model.annotations.Added((org.dmg.pmml.Version.XPMML))
@JsonProperty("x-mathContext")
private MathContext mathContext;
@XmlElement(name = "Extension", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("Extension")
private List extensions;
@XmlElement(name = "MiningSchema", namespace = "http://www.dmg.org/PMML-4_4", required = true)
@JsonProperty("MiningSchema")
private MiningSchema miningSchema;
@XmlElement(name = "Output", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("Output")
private Output output;
@XmlElement(name = "ModelStats", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("ModelStats")
private ModelStats modelStats;
@XmlElement(name = "ModelExplanation", namespace = "http://www.dmg.org/PMML-4_4")
@org.jpmml.model.annotations.Added((org.dmg.pmml.Version.PMML_4_0))
@JsonProperty("ModelExplanation")
private ModelExplanation modelExplanation;
@XmlElement(name = "Targets", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("Targets")
private Targets targets;
@XmlElement(name = "LocalTransformations", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("LocalTransformations")
private LocalTransformations localTransformations;
@XmlElement(name = "RegressionTable", namespace = "http://www.dmg.org/PMML-4_4", required = true)
@JsonProperty("RegressionTable")
private List regressionTables;
@XmlElement(name = "ModelVerification", namespace = "http://www.dmg.org/PMML-4_4")
@JsonProperty("ModelVerification")
private ModelVerification modelVerification;
private final static Boolean DEFAULT_SCORABLE = true;
private final static long serialVersionUID = 67371267L;
public RegressionModel() {
}
@ValueConstructor
public RegressionModel(
@org.jpmml.model.annotations.Property("miningFunction")
MiningFunction miningFunction,
@org.jpmml.model.annotations.Property("miningSchema")
MiningSchema miningSchema,
@org.jpmml.model.annotations.Property("regressionTables")
List regressionTables) {
this.miningFunction = miningFunction;
this.miningSchema = miningSchema;
this.regressionTables = regressionTables;
}
public String getModelName() {
return modelName;
}
public RegressionModel setModelName(
@org.jpmml.model.annotations.Property("modelName")
String modelName) {
this.modelName = modelName;
return this;
}
public MiningFunction getMiningFunction() {
return miningFunction;
}
public RegressionModel setMiningFunction(
@org.jpmml.model.annotations.Property("miningFunction")
MiningFunction miningFunction) {
this.miningFunction = miningFunction;
return this;
}
public String getAlgorithmName() {
return algorithmName;
}
public RegressionModel setAlgorithmName(
@org.jpmml.model.annotations.Property("algorithmName")
String algorithmName) {
this.algorithmName = algorithmName;
return this;
}
public RegressionModel.ModelType getModelType() {
return modelType;
}
public RegressionModel setModelType(
@org.jpmml.model.annotations.Property("modelType")
RegressionModel.ModelType modelType) {
this.modelType = modelType;
return this;
}
public FieldName getTargetField() {
return targetField;
}
public RegressionModel setTargetField(
@org.jpmml.model.annotations.Property("targetField")
FieldName targetField) {
this.targetField = targetField;
return this;
}
public RegressionModel.NormalizationMethod getNormalizationMethod() {
if (normalizationMethod == null) {
return RegressionModel.NormalizationMethod.NONE;
} else {
return normalizationMethod;
}
}
public RegressionModel setNormalizationMethod(
@org.jpmml.model.annotations.Property("normalizationMethod")
RegressionModel.NormalizationMethod normalizationMethod) {
this.normalizationMethod = normalizationMethod;
return this;
}
public boolean isScorable() {
if (scorable == null) {
return DEFAULT_SCORABLE;
} else {
return scorable;
}
}
public RegressionModel setScorable(
@org.jpmml.model.annotations.Property("scorable")
Boolean scorable) {
this.scorable = scorable;
return this;
}
public MathContext getMathContext() {
if (mathContext == null) {
return MathContext.DOUBLE;
} else {
return mathContext;
}
}
public RegressionModel setMathContext(
@org.jpmml.model.annotations.Property("mathContext")
MathContext mathContext) {
this.mathContext = mathContext;
return this;
}
@Override
public boolean hasExtensions() {
return ((this.extensions!= null)&&(this.extensions.size()> 0));
}
@Override
public List getExtensions() {
if (extensions == null) {
extensions = new ArrayList();
}
return this.extensions;
}
@Override
public RegressionModel addExtensions(Extension... extensions) {
getExtensions().addAll(Arrays.asList(extensions));
return this;
}
public MiningSchema getMiningSchema() {
return miningSchema;
}
public RegressionModel setMiningSchema(
@org.jpmml.model.annotations.Property("miningSchema")
MiningSchema miningSchema) {
this.miningSchema = miningSchema;
return this;
}
public Output getOutput() {
return output;
}
public RegressionModel setOutput(
@org.jpmml.model.annotations.Property("output")
Output output) {
this.output = output;
return this;
}
public ModelStats getModelStats() {
return modelStats;
}
public RegressionModel setModelStats(
@org.jpmml.model.annotations.Property("modelStats")
ModelStats modelStats) {
this.modelStats = modelStats;
return this;
}
public ModelExplanation getModelExplanation() {
return modelExplanation;
}
public RegressionModel setModelExplanation(
@org.jpmml.model.annotations.Property("modelExplanation")
ModelExplanation modelExplanation) {
this.modelExplanation = modelExplanation;
return this;
}
public Targets getTargets() {
return targets;
}
public RegressionModel setTargets(
@org.jpmml.model.annotations.Property("targets")
Targets targets) {
this.targets = targets;
return this;
}
public LocalTransformations getLocalTransformations() {
return localTransformations;
}
public RegressionModel setLocalTransformations(
@org.jpmml.model.annotations.Property("localTransformations")
LocalTransformations localTransformations) {
this.localTransformations = localTransformations;
return this;
}
public boolean hasRegressionTables() {
return ((this.regressionTables!= null)&&(this.regressionTables.size()> 0));
}
public List getRegressionTables() {
if (regressionTables == null) {
regressionTables = new ArrayList();
}
return this.regressionTables;
}
public RegressionModel addRegressionTables(RegressionTable... regressionTables) {
getRegressionTables().addAll(Arrays.asList(regressionTables));
return this;
}
public ModelVerification getModelVerification() {
return modelVerification;
}
public RegressionModel setModelVerification(
@org.jpmml.model.annotations.Property("modelVerification")
ModelVerification modelVerification) {
this.modelVerification = modelVerification;
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());
}
if ((status == VisitorAction.CONTINUE)&&hasRegressionTables()) {
status = PMMLObject.traverse(visitor, getRegressionTables());
}
if (status == VisitorAction.CONTINUE) {
status = PMMLObject.traverse(visitor, getModelVerification());
}
visitor.popParent();
}
if (status == VisitorAction.TERMINATE) {
return VisitorAction.TERMINATE;
}
return VisitorAction.CONTINUE;
}
@XmlType(name = "")
@XmlEnum
public enum ModelType
implements StringValue
{
@XmlEnumValue("linearRegression")
@JsonProperty("linearRegression")
LINEAR_REGRESSION("linearRegression"),
@XmlEnumValue("stepwisePolynomialRegression")
@JsonProperty("stepwisePolynomialRegression")
STEPWISE_POLYNOMIAL_REGRESSION("stepwisePolynomialRegression"),
@XmlEnumValue("logisticRegression")
@JsonProperty("logisticRegression")
LOGISTIC_REGRESSION("logisticRegression");
private final String value;
ModelType(String v) {
value = v;
}
@Override
public String value() {
return value;
}
public static RegressionModel.ModelType fromValue(String v) {
for (RegressionModel.ModelType c: RegressionModel.ModelType.values()) {
if (c.value.equals(v)) {
return c;
}
}
throw new IllegalArgumentException(v);
}
@Override
public String toString() {
return value();
}
}
@XmlType(name = "")
@XmlEnum
public enum NormalizationMethod
implements StringValue
{
@XmlEnumValue("none")
@JsonProperty("none")
NONE("none"),
@XmlEnumValue("simplemax")
@JsonProperty("simplemax")
SIMPLEMAX("simplemax"),
@XmlEnumValue("softmax")
@JsonProperty("softmax")
SOFTMAX("softmax"),
@XmlEnumValue("logit")
@JsonProperty("logit")
LOGIT("logit"),
@XmlEnumValue("probit")
@JsonProperty("probit")
PROBIT("probit"),
@XmlEnumValue("cloglog")
@JsonProperty("cloglog")
CLOGLOG("cloglog"),
@XmlEnumValue("exp")
@JsonProperty("exp")
EXP("exp"),
@XmlEnumValue("loglog")
@org.jpmml.model.annotations.Added((org.dmg.pmml.Version.PMML_3_1))
@JsonProperty("loglog")
LOGLOG("loglog"),
@XmlEnumValue("cauchit")
@org.jpmml.model.annotations.Added((org.dmg.pmml.Version.PMML_3_1))
@JsonProperty("cauchit")
CAUCHIT("cauchit");
private final String value;
NormalizationMethod(String v) {
value = v;
}
@Override
public String value() {
return value;
}
public static RegressionModel.NormalizationMethod fromValue(String v) {
for (RegressionModel.NormalizationMethod c: RegressionModel.NormalizationMethod.values()) {
if (c.value.equals(v)) {
return c;
}
}
throw new IllegalArgumentException(v);
}
@Override
public String toString() {
return value();
}
}
}
