com.pervasive.datarush.analytics.regression

Class PMMLRegressionClassificationModel

java.lang.Object

com.pervasive.datarush.analytics.pmml.PMMLModel

com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel

com.pervasive.datarush.analytics.regression.PMMLRegressionClassificationModel

public class PMMLRegressionClassificationModel
extends AbstractPMMLRegressionModel

Implementation of a 'maximum likelihood' classifier on top of regression models. The classifier has one RegressionTable for each category whose result on an input record is interpreted as the relative likelihood of the record belonging to that category. The predicted category is the one with the highest likelihood.

Nested Class Summary

Nested classes/interfaces inherited from class com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel

AbstractPMMLRegressionModel.CategoricalPredictor, AbstractPMMLRegressionModel.ModelType, AbstractPMMLRegressionModel.NormalizationMethod, AbstractPMMLRegressionModel.NumericPredictor, AbstractPMMLRegressionModel.RegressionTable

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

PMMLModel.MiningFunction

Field Summary

Fields

Modifier and Type	Field and Description
static String	FUNCTION_NAME

Constructor Summary

Constructors

Constructor and Description
PMMLRegressionClassificationModel() Create an empty model, to be filled in by the addCategory and addPredictor methods or by parse()
PMMLRegressionClassificationModel(Document document)
PMMLRegressionClassificationModel(PMMLModelSpec objectSpec)

Method Summary

Modifier and Type	Method and Description
void	addCategoricalPredictor(String categoryName, AbstractPMMLRegressionModel.CategoricalPredictor predictor) Adds a categorical predictor to the sub-model that predicts membership in a given category.
void	addCategory(String categoryName) Extend the classifier to predict membership in another class.
void	addNumericPredictor(String categoryName, AbstractPMMLRegressionModel.NumericPredictor predictor) Adds a numeric predictor to the sub-model that predicts membership in a given category.
protected void	buildModelElement(Element element) Subclasses must implement this method to fill-in the contents of the model element.
Set<String>	getCategories()
com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel.ValuePredictor	getCategoryPredictor(String category, RecordValued input, DoubleSettable target) Get the likelihood predictor for a particular category
protected void	parseModelElement(Element element) Parse the given model element into the respective model object.
void	setIntercept(String categoryName, double intercept) Sets the intercept of the submodel that predicts membership in a given category.

Methods inherited from class com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel

getModelElementName, getModelName, getNormalizationMethod, isScorable, logistic, setModelName, setNormalizationMethod, setScorable

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

Field Detail

FUNCTION_NAME

public static final String FUNCTION_NAME

See Also:

Constant Field Values

Constructor Detail

PMMLRegressionClassificationModel

public PMMLRegressionClassificationModel()

Create an empty model, to be filled in by the addCategory and addPredictor methods or by parse()

PMMLRegressionClassificationModel

public PMMLRegressionClassificationModel(PMMLModelSpec objectSpec)

PMMLRegressionClassificationModel

public PMMLRegressionClassificationModel(Document document)

Method Detail

buildModelElement

protected 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 AbstractPMMLRegressionModel

Parameters:

element - the model element

parseModelElement

protected void parseModelElement(Element element)

Description copied from class: AbstractPMMLRegressionModel

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.

Overrides:

parseModelElement in class AbstractPMMLRegressionModel

Parameters:

element - root element of model object

addCategory

public void addCategory(String categoryName)

Extend the classifier to predict membership in another class. Does nothing if it already predicts that class.

Parameters:

categoryName -

addNumericPredictor

public void addNumericPredictor(String categoryName,
                                AbstractPMMLRegressionModel.NumericPredictor predictor)

Adds a numeric predictor to the sub-model that predicts membership in a given category.

Parameters:

categoryName - which category the predictor's coefficient applies to

predictor - the predictor to add

addCategoricalPredictor

public void addCategoricalPredictor(String categoryName,
                                    AbstractPMMLRegressionModel.CategoricalPredictor predictor)

Adds a categorical predictor to the sub-model that predicts membership in a given category.

Parameters:

categoryName - which category the predictor's coefficient applies to

predictor - the predictor to add

setIntercept

public void setIntercept(String categoryName,
                         double intercept)

Sets the intercept of the submodel that predicts membership in a given category.

Parameters:

categoryName - which category the intercept belongs to

intercept - the value of the intercept

getCategories

public Set<String> getCategories()

Returns:

a collection of the categories recognized by this classification model.

getCategoryPredictor

public com.pervasive.datarush.analytics.regression.AbstractPMMLRegressionModel.ValuePredictor getCategoryPredictor(String category,
                                                                                                                   RecordValued input,
                                                                                                                   DoubleSettable target)

Get the likelihood predictor for a particular category

Parameters:

category - the category whose likelihood is to be predicted

input - the predictor's input record

target - the predictor's output

Returns:

a likelihood predictor