gate.creole.ml.weka
Class Wrapper

java.lang.Object
  gate.creole.ml.weka.Wrapper

All Implemented Interfaces:

AdvancedMLEngine, MLEngine, ActionsPublisher

public class Wrapper
extends Object
implements AdvancedMLEngine, ActionsPublisher

Wrapper class for the WEKA Machine Learning Engine.

See Also:

WEKA homepage

Nested Class Summary

protected class	Wrapper.LoadDatasetFromArffAction
protected class	Wrapper.LoadModelAction
protected class	Wrapper.SaveDatasetAsArffAction
protected class	Wrapper.SaveModelAction

Field Summary

protected List	actionsList
protected weka.classifiers.Classifier	classifier The WEKA classifier used by this wrapper
protected weka.core.Instances	dataset The dataset used for training
protected boolean	datasetChanged Marks whether the dataset was changed since the last time the classifier was built.
protected DatasetDefintion	datasetDefinition
protected File	datasetFile
protected boolean	onlyAccumulateDataset This variable is set when the ML configuration file has neither the classifier nor the output dataset file option.
protected org.jdom.Element	optionsElement The JDom element contaning the options fro this wrapper.
protected ProcessingResource	owner
protected StatusListener	sListener

Constructor Summary

Wrapper()

Method Summary

protected void	addTrainingInstance(weka.core.Instance instance)
void	addTrainingInstance(List attributeValues) Adds a new training instance to the dataset.
List	batchClassifyInstances(List instances) Some wrappers allow batch classification, but this one doesn't, so if it's ever called just inform the user about this by throwing an exception.
protected weka.core.Instance	buildInstance(List attributeValues) Constructs an instance valid for the current dataset from a list of attribute values.
Object	classifyInstance(List attributeValues) Classifies a new instance.
void	cleanUp() No clean up is needed for this wrapper, so this is just added because its in the interface.
protected Object	convertAttributeValue(double value)
List	getActions() Gets the list of actions that can be performed on this resource.
DatasetDefintion	getDatasetDefinition()
void	init() Initialises the classifier and prepares for running.
void	load(InputStream is) Loads the state of this engine from previously saved data.
void	loadDatasetFromArff(FileReader reader)
protected String[]	parseOptions(String optionsString)
void	save(OutputStream os) Saves the state of the engine for reuse at a later time.
void	saveDatasetAsARFF(FileWriter writer)
void	setDatasetDefinition(DatasetDefintion definition) Sets the definition for the dataset used.
void	setOptions(org.jdom.Element optionsElem) Sets the options from an XML JDom element.
void	setOwnerPR(ProcessingResource pr) Registers the PR using the engine with the engine itself.
boolean	supportsBatchMode() Returns true if the engine supports BatchMode, returns false otherwise.

Methods inherited from class java.lang.Object

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

Field Detail

datasetDefinition

protected DatasetDefintion datasetDefinition

classifier

protected weka.classifiers.Classifier classifier

The WEKA classifier used by this wrapper

dataset

protected weka.core.Instances dataset

The dataset used for training

optionsElement

protected org.jdom.Element optionsElement

The JDom element contaning the options fro this wrapper.

datasetChanged

protected boolean datasetChanged

Marks whether the dataset was changed since the last time the classifier was built.

datasetFile

protected File datasetFile

actionsList

protected List actionsList

owner

protected ProcessingResource owner

sListener

protected StatusListener sListener

onlyAccumulateDataset

protected boolean onlyAccumulateDataset

This variable is set when the ML configuration file has neither the classifier nor the output dataset file option. User is responsible for explicitly saving the dataset using the now uncommented SaveDatasetAsArff function / action.

Constructor Detail

Wrapper

public Wrapper()

Method Detail

cleanUp

public void cleanUp()

No clean up is needed for this wrapper, so this is just added because its in the interface.

Specified by:

cleanUp in interface MLEngine

setOptions

public void setOptions(org.jdom.Element optionsElem)

Description copied from interface: MLEngine

Sets the options from an XML JDom element.

Specified by:

setOptions in interface MLEngine

Parameters:

optionsElem - the JDom element containing the options from the configuration.

batchClassifyInstances

public List batchClassifyInstances(List instances)
                            throws ExecutionException

Some wrappers allow batch classification, but this one doesn't, so if it's ever called just inform the user about this by throwing an exception.

Specified by:

batchClassifyInstances in interface MLEngine

Parameters:

instances - This parameter is not used.

Returns:

Nothing is ever returned - an exception is always thrown.

Throws:

ExecutionException

addTrainingInstance

public void addTrainingInstance(List attributeValues)
                         throws ExecutionException

Description copied from interface: MLEngine

Adds a new training instance to the dataset.

Specified by:

addTrainingInstance in interface MLEngine

Parameters:

attributeValues - the list of attributes describing the instance. The elements in the list are String values that need to be interpreted according to the dataset definition: for nominal attributes the values will used as they are; for numeric attributes the values will be converted to double.

Throws:

ExecutionException

addTrainingInstance

protected void addTrainingInstance(weka.core.Instance instance)
                            throws ExecutionException

Throws:

ExecutionException

buildInstance

protected weka.core.Instance buildInstance(List attributeValues)
                                    throws ExecutionException

Constructs an instance valid for the current dataset from a list of attribute values.

Parameters:

attributeValues - the values for the attributes.

Returns:

an Instance value.

Throws:

ExecutionException

setDatasetDefinition

public void setDatasetDefinition(DatasetDefintion definition)

Description copied from interface: MLEngine

Sets the definition for the dataset used.

Specified by:

setDatasetDefinition in interface MLEngine

classifyInstance

public Object classifyInstance(List attributeValues)
                        throws ExecutionException

Description copied from interface: MLEngine

Classifies a new instance.

Specified by:

classifyInstance in interface MLEngine

Parameters:

attributeValues - the list of attributes describing the instance. The elements in the list are Object values that need to be interpreted according to the dataset definition. The value for the class element will be arbitrary.

Returns:

a String value for nominal and boolean attributes and a Double value for numeric attributes.

Throws:

ExecutionException

convertAttributeValue

protected Object convertAttributeValue(double value)

init

public void init()
          throws GateException

Initialises the classifier and prepares for running.

Specified by:

init in interface MLEngine

Throws:

GateException

parseOptions

protected String[] parseOptions(String optionsString)

load

public void load(InputStream is)
          throws IOException

Loads the state of this engine from previously saved data.

Parameters:

is -

Throws:

IOException

save

public void save(OutputStream os)
          throws IOException

Saves the state of the engine for reuse at a later time.

Parameters:

os -

Throws:

IOException

getActions

public List getActions()

Gets the list of actions that can be performed on this resource.

Specified by:

getActions in interface ActionsPublisher

Returns:

a List of Action objects (or null values)

setOwnerPR

public void setOwnerPR(ProcessingResource pr)

Registers the PR using the engine with the engine itself.

Specified by:

setOwnerPR in interface MLEngine

Parameters:

pr - the processing resource that owns this engine.

getDatasetDefinition

public DatasetDefintion getDatasetDefinition()

saveDatasetAsARFF

public void saveDatasetAsARFF(FileWriter writer)

loadDatasetFromArff

public void loadDatasetFromArff(FileReader reader)
                         throws IOException,
                                ExecutionException,
                                Exception

Throws:

IOException

ExecutionException

Exception

supportsBatchMode

public boolean supportsBatchMode()

Description copied from interface: AdvancedMLEngine

Returns true if the engine supports BatchMode, returns false otherwise.

Specified by:

supportsBatchMode in interface AdvancedMLEngine