Package adams.gui.tools.wekamultiexperimenter.experiment

Class AbstractExperiment.AbstractExperimentJob<T extends AbstractExperiment>

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.multiprocess.AbstractJob

adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob<T>

Type Parameters:

T - the type of experiment

All Implemented Interfaces:

CleanUpHandler, LoggingLevelHandler, LoggingSupporter, SizeOfHandler, Stoppable, StoppableWithFeedback, Job, Serializable

Direct Known Subclasses:

CrossValidationExperiment.CrossValidationExperimentJob, TrainTestSplitExperiment.TrainTestSplitExperimentJob

Enclosing class:

AbstractExperiment

public abstract static class AbstractExperiment.AbstractExperimentJob<T extends AbstractExperiment>
extends AbstractJob

For evaluating a single classifier/dataset combination.

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 classifier.
protected Index	m_ClassLabelIndex	the class label index.
protected weka.core.Instances	m_Data	the dataset.
protected T	m_Owner	the owner.
protected SpreadSheet	m_Results	the generated results.
protected int	m_Run	the run.

Fields inherited from class adams.multiprocess.AbstractJob

m_Complete, m_ExecutionError, m_JobCompleteListener, m_JobInfo, m_ProgressInfo, m_Stopped

Fields inherited from class adams.core.logging.LoggingObject

m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors

Constructor	Description
AbstractExperimentJob(T owner, int run, weka.classifiers.Classifier classifier, weka.core.Instances data)	Initializes the run.

Method Summary

Modifier and Type	Method	Description
protected void	addMetric(SpreadSheet results, String name, Object value)	Adds the metric to the results, automatically expands spreadsheet.
protected void	addMetrics(SpreadSheet results, int currentRun, weka.classifiers.Classifier cls, weka.core.Instances data, weka.classifiers.Evaluation eval)	Adds the metrics from the Evaluation object to the results.
protected abstract void	evaluate()	Performs the evaluation.
protected String	postProcessCheck()	Checks whether all post-conditions have been met.
protected String	preProcessCheck()	Checks whether all pre-conditions have been met.
protected void	process()	Does the actual execution of the job.
String	toString()	Returns a string representation of this job.

Methods inherited from class adams.multiprocess.AbstractJob

cleanUp, execute, getAdditionalErrorInformation, getExecutionError, getJobCompleteListener, getJobInfo, getProgressInfo, hasExecutionError, isComplete, isStopped, jobCompleted, setJobCompleteListener, setJobInfo, setProgressInfo, stopExecution

Methods inherited from class adams.core.logging.CustomLoggingLevelObject

setLoggingLevel

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.logging.LoggingLevelHandler

getLoggingLevel

Methods inherited from interface adams.core.logging.LoggingSupporter

getLogger, isLoggingEnabled

Field Detail

m_Owner

protected T extends AbstractExperiment m_Owner

the owner.

m_Run

protected int m_Run

the run.

m_Classifier

protected weka.classifiers.Classifier m_Classifier

the classifier.

m_Data

protected weka.core.Instances m_Data

the dataset.

m_ClassLabelIndex

protected Index m_ClassLabelIndex

the class label index.

m_Results

protected SpreadSheet m_Results

the generated results.

Constructor Detail

AbstractExperimentJob

public AbstractExperimentJob(T owner,
                             int run,
                             weka.classifiers.Classifier classifier,
                             weka.core.Instances data)

Initializes the run.

Parameters:

owner - the owning experiment

run - the current run

classifier - the classifier to evaluate

data - the data to use for evaluation

Method Detail

addMetric

protected void addMetric(SpreadSheet results,
                         String name,
                         Object value)

Adds the metric to the results, automatically expands spreadsheet.

Parameters:

results - the results to add the metrics to

name - the name

value - the value

addMetrics

protected void addMetrics(SpreadSheet results,
                          int currentRun,
                          weka.classifiers.Classifier cls,
                          weka.core.Instances data,
                          weka.classifiers.Evaluation eval)

Adds the metrics from the Evaluation object to the results.

Parameters:

results - the results to add the metrics to

currentRun - the current run

cls - the classifier to evaluate

data - the dataset to evaluate on

eval - the Evaluation object to add

preProcessCheck

protected String preProcessCheck()

Checks whether all pre-conditions have been met.

Specified by:

preProcessCheck in class AbstractJob

Returns:

null if everything is OK, otherwise an error message

evaluate

protected abstract void evaluate()

Performs the evaluation.

process

protected void process()
                throws Exception

Does the actual execution of the job.

Specified by:

process in class AbstractJob

Throws:

Exception - if fails to execute job

postProcessCheck

protected String postProcessCheck()

Checks whether all post-conditions have been met.

Specified by:

postProcessCheck in class AbstractJob

Returns:

null if everything is OK, otherwise an error message

toString

public String toString()

Returns a string representation of this job.

Specified by:

toString in class AbstractJob

Returns:

the job as string