Package adams.ml.model.regression

Class WekaRegressor

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

adams.ml.model.regression.AbstractRegressor

adams.ml.model.regression.WekaRegressor

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, SizeOfHandler, CapabilitiesHandler, Algorithm<RegressionModel>, Regressor, Serializable

public class WekaRegressor
extends AbstractRegressor

Wraps around a Weka classifier that handles numeric classes (= regression).

-logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
    The logging level for outputting errors and debugging output.
    default: WARNING
 

-strict-capabilities <boolean> (property: strictCapabilities)
    If enabled, a strict capabilities test is performed; otherwise, it is attempted 
    to adjust the data to fit the algorithm's capabilities.
    default: false
 

-classifier <weka.classifiers.Classifier> (property: classifier)
    The classifier to use.
    default: weka.classifiers.functions.LinearRegressionJ -S 0 -R 1.0E-8 -num-decimal-places 4
 

Version:

$Revision$

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected weka.classifiers.Classifier	m_Classifier	the weka classifier to use.

Fields inherited from class adams.ml.model.regression.AbstractRegressor

m_StrictCapabilities

Fields inherited from class adams.core.option.AbstractOptionHandler

m_OptionManager

Fields inherited from class adams.core.logging.LoggingObject

m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors

Constructor	Description
WekaRegressor()

Method Summary

Modifier and Type	Method	Description
String	classifierTipText()	Returns the tip text for this property.
void	defineOptions()	Adds options to the internal list of options.
protected RegressionModel	doBuildModel(Dataset data)	Builds a model from the data.
Capabilities	getCapabilities()	Returns the algorithm's capabilities in terms of data.
weka.classifiers.Classifier	getClassifier()	Returns the classifier to use.
String	globalInfo()	Returns a string describing the object.
void	setClassifier(weka.classifiers.Classifier value)	Sets the classifier to use.

Methods inherited from class adams.ml.model.regression.AbstractRegressor

buildModel, check, getStrictCapabilities, handles, setStrictCapabilities, strictCapabilitiesTipText

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, setLoggingLevel, toCommandLine, toString

Methods inherited from class adams.core.logging.LoggingObject

configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface adams.core.Destroyable

destroy

Methods inherited from interface adams.core.logging.LoggingLevelHandler

getLoggingLevel

Methods inherited from interface adams.core.option.OptionHandler

cleanUpOptions, getOptionManager, toCommandLine

Field Detail

m_Classifier

protected weka.classifiers.Classifier m_Classifier

the weka classifier to use.

Constructor Detail

WekaRegressor

public WekaRegressor()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

Specified by:

globalInfo in interface GlobalInfoSupporter

Specified by:

globalInfo in class AbstractOptionHandler

Returns:

a description suitable for displaying in the gui

defineOptions

public void defineOptions()

Adds options to the internal list of options.

Specified by:

defineOptions in interface OptionHandler

Overrides:

defineOptions in class AbstractRegressor

setClassifier

public void setClassifier(weka.classifiers.Classifier value)

Sets the classifier to use.

Parameters:

value - the classifier

getClassifier

public weka.classifiers.Classifier getClassifier()

Returns the classifier to use.

Returns:

the classifier

classifierTipText

public String classifierTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

getCapabilities

public Capabilities getCapabilities()

Returns the algorithm's capabilities in terms of data.

Specified by:

getCapabilities in interface Algorithm<RegressionModel>

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractRegressor

Returns:

the algorithm's capabilities

doBuildModel

protected RegressionModel doBuildModel(Dataset data)
                                throws Exception

Builds a model from the data.

Specified by:

doBuildModel in class AbstractRegressor

Parameters:

data - the data to use for building the model

Returns:

the generated model

Throws:

Exception - if the build fails