public class ClassifierSplitEvaluator extends java.lang.Object implements SplitEvaluator, OptionHandler, AdditionalMeasureProducer, RevisionHandler
-W <class name> The full class name of the classifier. eg: weka.classifiers.bayes.NaiveBayes
-C <index> The index of the class for which IR statistics are to be output. (default 1)
-I <index> The index of an attribute to output in the results. This attribute should identify an instance in order to know which instances are in the test set of a cross validation. if 0 no output (default 0).
-P Add target and prediction columns to the result for each fold.
-no-size Skips the determination of sizes (train/test/classifier) (default: sizes are determined)
Options specific to classifier weka.classifiers.rules.ZeroR:
-D If set, classifier is run in debug mode and may output additional info to the consoleAll options after -- will be passed to the classifier.
Constructor and Description |
---|
ClassifierSplitEvaluator()
No args constructor.
|
Modifier and Type | Method and Description |
---|---|
java.lang.String |
classifierTipText()
Returns the tip text for this property
|
java.util.Enumeration<java.lang.String> |
enumerateMeasures()
Returns an enumeration of any additional measure names that might be in the
classifier
|
int |
getAttributeID()
Get the index of Attibute Identifying the instances
|
int |
getClassForIRStatistics()
Get the value of ClassForIRStatistics.
|
Classifier |
getClassifier()
Get the value of Classifier.
|
java.lang.Object[] |
getKey()
Gets the key describing the current SplitEvaluator.
|
java.lang.String[] |
getKeyNames()
Gets the names of each of the key columns produced for a single run.
|
java.lang.Object[] |
getKeyTypes()
Gets the data types of each of the key columns produced for a single run.
|
double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure
|
boolean |
getNoSizeDetermination()
Returns whether the size determination (train/test/classifer) is skipped.
|
java.lang.String[] |
getOptions()
Gets the current settings of the Classifier.
|
boolean |
getPredTargetColumn() |
java.lang.String |
getRawResultOutput()
Gets the raw output from the classifier
|
java.lang.Object[] |
getResult(Instances train,
Instances test)
Gets the results for the supplied train and test datasets.
|
java.lang.String[] |
getResultNames()
Gets the names of each of the result columns produced for a single run.
|
java.lang.Object[] |
getResultTypes()
Gets the data types of each of the result columns produced for a single
run.
|
java.lang.String |
getRevision()
Returns the revision string.
|
java.lang.String |
globalInfo()
Returns a string describing this split evaluator
|
java.util.Enumeration<Option> |
listOptions()
Returns an enumeration describing the available options..
|
java.lang.String |
noSizeDeterminationTipText()
Returns the tip text for this property
|
void |
setAdditionalMeasures(java.lang.String[] additionalMeasures)
Set a list of method names for additional measures to look for in
Classifiers.
|
void |
setAttributeID(int v)
Set the index of Attibute Identifying the instances
|
void |
setClassForIRStatistics(int v)
Set the value of ClassForIRStatistics.
|
void |
setClassifier(Classifier newClassifier)
Sets the classifier.
|
void |
setClassifierName(java.lang.String newClassifierName)
Set the Classifier to use, given it's class name.
|
void |
setNoSizeDetermination(boolean value)
Sets whether the size determination (train/test/classifer) is skipped.
|
void |
setOptions(java.lang.String[] options)
Parses a given list of options.
|
void |
setPredTargetColumn(boolean v)
Set the flag for prediction and target output.
|
java.lang.String |
toString()
Returns a text description of the split evaluator.
|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
makeCopy
public java.lang.String globalInfo()
public java.util.Enumeration<Option> listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-W <class name> The full class name of the classifier. eg: weka.classifiers.bayes.NaiveBayes
-C <index> The index of the class for which IR statistics are to be output. (default 1)
-I <index> The index of an attribute to output in the results. This attribute should identify an instance in order to know which instances are in the test set of a cross validation. if 0 no output (default 0).
-P Add target and prediction columns to the result for each fold.
-no-size Skips the determination of sizes (train/test/classifier) (default: sizes are determined)
Options specific to classifier weka.classifiers.rules.ZeroR:
-D If set, classifier is run in debug mode and may output additional info to the consoleAll options after -- will be passed to the classifier.
setOptions
in interface OptionHandler
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public void setAdditionalMeasures(java.lang.String[] additionalMeasures)
setAdditionalMeasures
in interface SplitEvaluator
additionalMeasures
- a list of method namespublic java.util.Enumeration<java.lang.String> enumerateMeasures()
enumerateMeasures
in interface AdditionalMeasureProducer
public double getMeasure(java.lang.String additionalMeasureName)
getMeasure
in interface AdditionalMeasureProducer
additionalMeasureName
- the name of the measure to query for its valuejava.lang.IllegalArgumentException
- if the named measure is not supportedpublic java.lang.Object[] getKeyTypes()
getKeyTypes
in interface SplitEvaluator
public java.lang.String[] getKeyNames()
getKeyNames
in interface SplitEvaluator
public java.lang.Object[] getKey()
getKey
in interface SplitEvaluator
public java.lang.Object[] getResultTypes()
getResultTypes
in interface SplitEvaluator
public java.lang.String[] getResultNames()
getResultNames
in interface SplitEvaluator
public java.lang.Object[] getResult(Instances train, Instances test) throws java.lang.Exception
getResult
in interface SplitEvaluator
train
- the training Instances.test
- the testing Instances.java.lang.Exception
- if a problem occurs while getting the resultspublic java.lang.String classifierTipText()
public Classifier getClassifier()
public void setClassifier(Classifier newClassifier)
newClassifier
- the new classifier to use.public int getClassForIRStatistics()
public void setClassForIRStatistics(int v)
v
- Value to assign to ClassForIRStatistics.public int getAttributeID()
public void setAttributeID(int v)
v
- index the attribute to outputpublic boolean getPredTargetColumn()
public void setPredTargetColumn(boolean v)
v
- true if the 2 columns have to be outputed. false otherwise.public boolean getNoSizeDetermination()
public void setNoSizeDetermination(boolean value)
value
- true if to determine sizespublic java.lang.String noSizeDeterminationTipText()
public void setClassifierName(java.lang.String newClassifierName) throws java.lang.Exception
newClassifierName
- the Classifier class name.java.lang.Exception
- if the class name is invalid.public java.lang.String getRawResultOutput()
getRawResultOutput
in interface SplitEvaluator
public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface RevisionHandler