Package adams.ml.model.regression

Class AbstractRegressor

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

adams.ml.model.regression.AbstractRegressor

All Implemented Interfaces:

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

Direct Known Subclasses:

WekaRegressor

public abstract class AbstractRegressor
extends AbstractOptionHandler
implements Regressor

Ancestor for regression algorithms.

Version:

$Revision$

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected boolean	m_StrictCapabilities	whether to use strict capability tests.

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
AbstractRegressor()

Method Summary

Modifier and Type	Method	Description
RegressionModel	buildModel(Dataset data)	Builds a model from the data.
protected Dataset	check(Dataset data)	Performs checks on the data.
void	defineOptions()	Adds options to the internal list of options.
protected abstract RegressionModel	doBuildModel(Dataset data)	Builds a model from the data.
Capabilities	getCapabilities()	Returns the algorithm's capabilities in terms of data.
boolean	getStrictCapabilities()	Returns whether to use a strict capabilities check.
String	handles(Dataset data, boolean strict)	Checks whether the data can be handled.
void	setStrictCapabilities(boolean value)	Sets whether to use a strict capabilities check.
String	strictCapabilitiesTipText()	Returns the tip text for this property.

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, globalInfo, 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_StrictCapabilities

protected boolean m_StrictCapabilities

whether to use strict capability tests.

Constructor Detail

AbstractRegressor

public AbstractRegressor()

Method Detail

defineOptions

public void defineOptions()

Adds options to the internal list of options.

Specified by:

defineOptions in interface OptionHandler

Overrides:

defineOptions in class AbstractOptionHandler

setStrictCapabilities

public void setStrictCapabilities(boolean value)

Sets whether to use a strict capabilities check.

Parameters:

value - true if to use strict check

getStrictCapabilities

public boolean getStrictCapabilities()

Returns whether to use a strict capabilities check.

Returns:

true if to use strict check

strictCapabilitiesTipText

public String strictCapabilitiesTipText()

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

Returns:

the algorithm's capabilities

handles

public String handles(Dataset data,
                      boolean strict)

Checks whether the data can be handled.

Specified by:

handles in interface Algorithm<RegressionModel>

Parameters:

data - the data to check

strict - whether to perform a strict check

Returns:

null if data can be handled, otherwise error message

check

protected Dataset check(Dataset data)
                 throws Exception

Performs checks on the data.

Parameters:

data - the data to check

Returns:

the potentially adjusted data

Throws:

Exception - if checks fail

doBuildModel

protected abstract RegressionModel doBuildModel(Dataset data)
                                         throws Exception

Builds a model from the data.

Parameters:

data - the data to use for building the model

Returns:

the generated model

Throws:

Exception - if the build fails

buildModel

public RegressionModel buildModel(Dataset data)
                           throws Exception

Builds a model from the data.

Specified by:

buildModel in interface Algorithm<RegressionModel>

Parameters:

data - the data to use for building the model

Returns:

the generated model

Throws:

Exception - if the build fails