weka.classifiers.pmml.producer

Class AbstractPMMLProducerHelper

java.lang.Object

weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

Direct Known Subclasses:

LogisticProducerHelper

public abstract class AbstractPMMLProducerHelper
extends java.lang.Object

Abstract base class for PMMLProducer helper classes to extend.

Version:

$Revision: $

Author:

David Persons, Mark Hall (mhall{[at]}pentaho{[dot]}com)

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	PMML_VERSION PMML version that the jaxbbindings were created from

Constructor Summary

Constructors

Constructor and Description
AbstractPMMLProducerHelper()

Method Summary

Modifier and Type	Method and Description
static void	addDataDictionary(Instances trainHeader, PMML pmml) Adds a data dictionary to the supplied PMML object.
static java.lang.String[]	getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute(Instances train, Attribute derived) Extracts the original attribute name and value from the name of a binary indicator attribute created by unsupervised NominalToBinary.
static OPTYPE	getOPTYPE(int wekaType) Returns an OPTYPE for a weka attribute type.
static PMML	initPMML() Initializes a PMML object with header information.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

PMML_VERSION

public static final java.lang.String PMML_VERSION

PMML version that the jaxbbindings were created from

See Also:

Constant Field Values

Constructor Detail

AbstractPMMLProducerHelper

public AbstractPMMLProducerHelper()

Method Detail

initPMML

public static PMML initPMML()

Initializes a PMML object with header information.

Returns:

an initialized PMML object

addDataDictionary

public static void addDataDictionary(Instances trainHeader,
                                     PMML pmml)

Adds a data dictionary to the supplied PMML object.

Parameters:

trainHeader - the training data header - i.e. the header of the data that enters the buildClassifier() method of the model in question

pmml - the PMML object to add the data dictionary to

getOPTYPE

public static OPTYPE getOPTYPE(int wekaType)

Returns an OPTYPE for a weka attribute type. Note that PMML only supports categorical, continuous and ordinal types.

Parameters:

wekaType - the type of the weka attribute

Returns:

the PMML type

getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute

public static java.lang.String[] getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute(Instances train,
                                                                                                Attribute derived)

Extracts the original attribute name and value from the name of a binary indicator attribute created by unsupervised NominalToBinary. Handles the case where one or more equals signs might be present in the original attribute name.

Parameters:

train - the original, unfiltered training header

derived - the derived attribute from which to extract the original name and value from the name created by NominalToBinary.

Returns: