com.pervasive.datarush.analytics.regression

Class AbstractPMMLRegressionModel

java.lang.Object

com.pervasive.datarush.analytics.pmml.PMMLModel

com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel

Direct Known Subclasses:

PMMLRegressionClassificationModel, PMMLRegressionModel

public abstract class AbstractPMMLRegressionModel
extends PMMLModel

A representation of features found in PMML regressionModel elements that do not depend on its attributes.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AbstractPMMLRegressionModel.CategoricalPredictor
static class	AbstractPMMLRegressionModel.ModelType The possible values of the ModelType attribute of a PMML regressionModel.
static class	AbstractPMMLRegressionModel.NormalizationMethod The normalization methods used.
static class	AbstractPMMLRegressionModel.NumericPredictor Capture information about numeric predictor values.
protected static class	AbstractPMMLRegressionModel.RegressionTable

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

PMMLModel.MiningFunction

Constructor Summary

Constructors

Constructor and Description
AbstractPMMLRegressionModel()
AbstractPMMLRegressionModel(PMMLModelSpec objectSpec)

Method Summary

Methods

Modifier and Type	Method and Description
protected abstract void	buildModelElement(Element element) Subclasses must implement this method to fill-in the contents of the model element.
protected String	getModelElementName() Return the element name of the primary model element associated with this PMML
String	getModelName()
AbstractPMMLRegressionModel.NormalizationMethod	getNormalizationMethod()
boolean	isScorable()
static double	logistic(double value) An implementation of the logit model's normalization function.
protected void	parseModelElement(Element element) Parse the given model element into the respective model object.
void	setModelName(String modelName)
void	setNormalizationMethod(AbstractPMMLRegressionModel.NormalizationMethod normalizationMethod)
void	setScorable(boolean b) Whether a consumer can use the model to make predictions (set to false to indicate the model is for information purposes only.)

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

AbstractPMMLRegressionModel

public AbstractPMMLRegressionModel(PMMLModelSpec objectSpec)

AbstractPMMLRegressionModel

public AbstractPMMLRegressionModel()

Method Detail

logistic

public static double logistic(double value)

An implementation of the logit model's normalization function.

Parameters:

value - the real number to normalize.

Returns:

the normalized value, between 0 and 1, or NaN if the input value is not-a-number.

setScorable

public void setScorable(boolean b)

Whether a consumer can use the model to make predictions (set to false to indicate the model is for information purposes only.)

Parameters:

b -

isScorable

public boolean isScorable()

Returns:

whether the model should be used for predictions.

setNormalizationMethod

public void setNormalizationMethod(AbstractPMMLRegressionModel.NormalizationMethod normalizationMethod)

Parameters:

normalizationMethod - the normalization method to use to transform the linear result to a prediction

getNormalizationMethod

public AbstractPMMLRegressionModel.NormalizationMethod getNormalizationMethod()

Returns:

the normalization method used to transform the linear result to a prediction

setModelName

public void setModelName(String modelName)

Parameters:

modelName - the desired "modelName" PMML attribute

getModelName

public String getModelName()

Returns:

the current value of the "modelName" PMML attribute. The modelName is a brief natural-language description of the model.

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

buildModelElement

protected abstract 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

parseModelElement

protected void parseModelElement(Element element)

Parse the given model element into the respective model object. This implementation only reads the normalizationMethod and scorable attributes. Subclasses SHOULD override this and are responsible for Regression Tables and the function name and target field attributes.

Specified by:

parseModelElement in class PMMLModel

Parameters:

element - root element of model object

Throws:

UnsupportedPPMMLException - if the normalization method is not represented in the NormalizationMethod enum.