public class AutoWEKAClassifier
extends weka.classifiers.AbstractClassifier
implements weka.core.AdditionalMeasureProducer
| Modifier and Type | Field and Description |
|---|---|
protected weka.attributeSelection.AttributeSelection |
as
The chosen attribute selection method.
|
protected java.lang.String[] |
attributeEvalArgs
The arguments of the chosen attribute evaluation method.
|
protected java.lang.String |
attributeEvalClass
The class of the chosen attribute evaluation.
|
protected java.lang.String[] |
attributeSearchArgs
The arguments of the chosen attribute search method.
|
protected java.lang.String |
attributeSearchClass
The class of the chosen attribute search method.
|
protected weka.classifiers.Classifier |
classifier
The chosen classifier.
|
protected java.lang.String[] |
classifierArgs
The arguments of the chosen classifier.
|
protected java.lang.String |
classifierClass
The class of the chosen classifier.
|
protected double |
estimatedError
The estimated error of the chosen method.
|
protected weka.classifiers.Evaluation |
eval
The evaluation for the best classifier.
|
protected static java.lang.String |
expName
The internal name of the experiment.
|
protected java.lang.String |
extraArgs
The extra arguments for Auto-WEKA.
|
protected int |
memLimit
The memory limit for running classifiers.
|
protected static java.lang.String |
msExperimentPath
The path to the internal Auto-WEKA files.
|
protected weka.classifiers.meta.AutoWEKAClassifier.Resampling |
resampling
The internal evaluation method.
|
protected java.lang.String |
resamplingArgs
The arguments to the evaluation method.
|
protected int |
seed
The random seed.
|
protected int |
timeLimit
The time limit for running Auto-WEKA.
|
| Constructor and Description |
|---|
AutoWEKAClassifier()
Constructs a new AutoWEKAClassifier.
|
| Modifier and Type | Method and Description |
|---|---|
void |
buildClassifier(weka.core.Instances is)
Find the best classifier, arguments, and attribute selection for the data.
|
double |
classifyInstance(weka.core.Instance i)
Calculates the class membership for the given test instance.
|
double[] |
distributionForInstance(weka.core.Instance i)
Calculates the class membership probabilities for the given test instance.
|
java.util.Enumeration |
enumerateMeasures()
Returns an enumeration of the additional measure names
|
weka.core.Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
|
double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure
|
int |
getMemLimit()
Get the memory limit.
|
java.lang.String[] |
getOptions()
Returns the options of the current setup.
|
int |
getSeed()
Get the random seed.
|
weka.core.TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing
detailed information about the technical background of this class,
e.g., paper reference or book this class is based on.
|
int |
getTimeLimit()
Get the time limit.
|
java.lang.String |
globalInfo()
This will return a string describing the classifier.
|
java.util.Enumeration<weka.core.Option> |
listOptions()
Gets an enumeration describing the available options.
|
static void |
main(java.lang.String[] argv)
Main method for testing this class.
|
double |
measureEstimatedError()
Returns the error estimated during Auto-WEKA's internal evaluation.
|
java.lang.String |
memLimitTipText()
Returns the tip text for this property.
|
java.lang.String |
seedTipText()
Returns the tip text for this property.
|
void |
setLog(weka.gui.Logger log)
Set the WEKA logger.
|
void |
setMemLimit(int ml)
Set the memory limit.
|
void |
setOptions(java.lang.String[] options)
Set the options for the current setup.
|
void |
setSeed(int s)
Set the random seed.
|
void |
setTimeLimit(int tl)
Set the time limit.
|
java.lang.String |
timeLimitTipText()
Returns the tip text for this property.
|
java.lang.String |
toString()
This will return a string describing the classifier.
|
batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlacesprotected weka.classifiers.Classifier classifier
protected weka.attributeSelection.AttributeSelection as
protected java.lang.String classifierClass
protected java.lang.String[] classifierArgs
protected java.lang.String attributeSearchClass
protected java.lang.String[] attributeSearchArgs
protected java.lang.String attributeEvalClass
protected java.lang.String[] attributeEvalArgs
protected static java.lang.String msExperimentPath
protected static java.lang.String expName
protected int seed
protected int timeLimit
protected int memLimit
protected weka.classifiers.meta.AutoWEKAClassifier.Resampling resampling
protected java.lang.String resamplingArgs
protected java.lang.String extraArgs
protected double estimatedError
protected weka.classifiers.Evaluation eval
public AutoWEKAClassifier()
public static void main(java.lang.String[] argv)
argv - should contain command line options (see setOptions)public void buildClassifier(weka.core.Instances is)
throws java.lang.Exception
buildClassifier in interface weka.classifiers.Classifierdata - the training data to be used for selecting and tuning the
classifier.java.lang.Exception - if the classifier could not be built successfully.public double classifyInstance(weka.core.Instance i)
throws java.lang.Exception
classifyInstance in interface weka.classifiers.ClassifierclassifyInstance in class weka.classifiers.AbstractClassifierinstance - the instance to be classifiedjava.lang.Exception - if instance could not be classified successfullypublic double[] distributionForInstance(weka.core.Instance i)
throws java.lang.Exception
distributionForInstance in interface weka.classifiers.ClassifierdistributionForInstance in class weka.classifiers.AbstractClassifierinstance - the instance to be classifiedjava.lang.Exception - if instance could not be classified successfully.public java.util.Enumeration<weka.core.Option> listOptions()
listOptions in interface weka.core.OptionHandlerlistOptions in class weka.classifiers.AbstractClassifierpublic java.lang.String[] getOptions()
getOptions in interface weka.core.OptionHandlergetOptions in class weka.classifiers.AbstractClassifierpublic void setOptions(java.lang.String[] options)
throws java.lang.Exception
setOptions in interface weka.core.OptionHandlersetOptions in class weka.classifiers.AbstractClassifieroptions - the new optionsjava.lang.Exceptionpublic void setSeed(int s)
s - The random seed.public int getSeed()
public java.lang.String seedTipText()
public void setTimeLimit(int tl)
tl - The time limit in minutes.public int getTimeLimit()
public java.lang.String timeLimitTipText()
public void setMemLimit(int ml)
ml - The memory limit in MiB.public int getMemLimit()
public java.lang.String memLimitTipText()
public void setLog(weka.gui.Logger log)
public weka.core.Capabilities getCapabilities()
getCapabilities in interface weka.classifiers.ClassifiergetCapabilities in interface weka.core.CapabilitiesHandlergetCapabilities in class weka.classifiers.AbstractClassifierpublic weka.core.TechnicalInformation getTechnicalInformation()
public java.lang.String globalInfo()
public java.lang.String toString()
toString in class java.lang.Objectpublic double measureEstimatedError()
public java.util.Enumeration enumerateMeasures()
enumerateMeasures in interface weka.core.AdditionalMeasureProducerpublic double getMeasure(java.lang.String additionalMeasureName)
getMeasure in interface weka.core.AdditionalMeasureProduceradditionalMeasureName - the name of the measure to query for its valuejava.lang.IllegalArgumentException - if the named measure is not supported