public class PMMLRegressionModel extends AbstractPMMLRegressionModel
AbstractPMMLRegressionModel.CategoricalPredictor, AbstractPMMLRegressionModel.ModelType, AbstractPMMLRegressionModel.NormalizationMethod, AbstractPMMLRegressionModel.NumericPredictor, AbstractPMMLRegressionModel.RegressionTable
PMMLModel.MiningFunction
Constructor and Description |
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PMMLRegressionModel(Document document)
Construct the PMML model directly from an XML document.
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PMMLRegressionModel(PMMLModelSpec objectSpec)
Construct the PMML model from a model specification.
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Modifier and Type | Method and Description |
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void |
addCategoricalPredictor(AbstractPMMLRegressionModel.CategoricalPredictor categoricalPredictor)
Adds a categorical predictor to the PMML model.
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void |
addNumericPredictor(AbstractPMMLRegressionModel.NumericPredictor numericPredictor)
Add a numeric predictor to the PMML model.
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protected void |
buildModelElement(Element element)
Subclasses must implement this method to fill-in the contents
of the model element.
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List<AbstractPMMLRegressionModel.CategoricalPredictor> |
getCategoricalPredictor(String indepVarName)
Get the categorical predictor for the given independent variable.
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List<AbstractPMMLRegressionModel.CategoricalPredictor> |
getCategoricalPredictors() |
double |
getIntercept()
Get the intercept value.
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AbstractPMMLRegressionModel.NumericPredictor |
getNumericPredictor(String indepVarName)
Get the numeric predictor for the given independent variable.
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List<AbstractPMMLRegressionModel.NumericPredictor> |
getNumericPredictors()
Return the list of numeric predictors for this model.
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com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel.ValuePredictor |
getValuePredictor(RecordValued input,
DoubleSettable target)
Get a value predictor for this model.
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protected void |
parseModelElement(Element element)
Parse the given model element into the respective model object.
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void |
setIntercept(double value)
Set the intercept value.
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void |
setInterceptDegreesOfFreedom(int value)
Set the intercept's degrees of freedom.
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void |
setInterceptPValue(double value)
Set the intercept's p value.
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void |
setInterceptStandardError(double value)
Set the intercept's standard error.
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void |
setInterceptTTest(double value)
Set the intercept's t test.
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getModelElementName, getModelName, getNormalizationMethod, isScorable, logistic, setModelName, setNormalizationMethod, setScorable
findModelElement, getAnnotationText, getModelExplanation, getModelSpec, getVersion, parse, setAnnotationText, setModelExplanation, setVersion, toPMML
public PMMLRegressionModel(PMMLModelSpec objectSpec)
objectSpec
- model specificationpublic PMMLRegressionModel(Document document)
document
- XML document containing PMMLpublic void setIntercept(double value)
value
- intercept valuepublic void setInterceptDegreesOfFreedom(int value)
value
- interceptDegreesOfFreedom valuepublic void setInterceptStandardError(double value)
value
- interceptStandardError valuepublic void setInterceptTTest(double value)
value
- interceptTTest valuepublic void setInterceptPValue(double value)
value
- interceptPValue valuepublic double getIntercept()
public void addNumericPredictor(AbstractPMMLRegressionModel.NumericPredictor numericPredictor)
numericPredictor
- numeric predictorpublic List<AbstractPMMLRegressionModel.NumericPredictor> getNumericPredictors()
public AbstractPMMLRegressionModel.NumericPredictor getNumericPredictor(String indepVarName)
indepVarName
- name of the independent variablepublic void addCategoricalPredictor(AbstractPMMLRegressionModel.CategoricalPredictor categoricalPredictor)
categoricalPredictor
- the Categorical Predictor elementpublic List<AbstractPMMLRegressionModel.CategoricalPredictor> getCategoricalPredictors()
public List<AbstractPMMLRegressionModel.CategoricalPredictor> getCategoricalPredictor(String indepVarName)
indepVarName
- name of the independent variablepublic com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel.ValuePredictor getValuePredictor(RecordValued input, DoubleSettable target)
input
- input data source containing independent data valuestarget
- output field containing result of predictionprotected void buildModelElement(Element element)
PMMLModel
buildModelElement
in class AbstractPMMLRegressionModel
element
- the model elementprotected void parseModelElement(Element element)
AbstractPMMLRegressionModel
parseModelElement
in class AbstractPMMLRegressionModel
element
- root element of model objectCopyright © 2016 Actian Corporation. All rights reserved.