程序包 weka.experiment

类 ClassifierSplitEvaluator

java.lang.Object
weka.experiment.ClassifierSplitEvaluator
所有已实现的接口:
Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, SplitEvaluator
直接已知子类:
CostSensitiveClassifierSplitEvaluator

public class ClassifierSplitEvaluator extends Object implements SplitEvaluator, OptionHandler, AdditionalMeasureProducer, RevisionHandler
A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.

Valid options are:

 -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.
 
 Options specific to classifier weka.classifiers.rules.ZeroR:
 
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 
All options after -- will be passed to the classifier.
版本:
$Revision: 11198 $
作者:
Len Trigg (trigg@cs.waikato.ac.nz)
另请参阅:
  • 构造器详细资料

    • ClassifierSplitEvaluator

      public ClassifierSplitEvaluator()
      No args constructor.
  • 方法详细资料

    • globalInfo

      public String globalInfo()
      Returns a string describing this split evaluator
      返回:
      a description of the split evaluator suitable for displaying in the explorer/experimenter gui
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options..
      指定者:
      listOptions 在接口中 OptionHandler
      返回:
      an enumeration of all the available options.
    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are:

       -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.
       
       Options specific to classifier weka.classifiers.rules.ZeroR:
       
       -D
        If set, classifier is run in debug mode and
        may output additional info to the console
       
      All options after -- will be passed to the classifier.
      指定者:
      setOptions 在接口中 OptionHandler
      参数:
      options - the list of options as an array of strings
      抛出:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the Classifier.
      指定者:
      getOptions 在接口中 OptionHandler
      返回:
      an array of strings suitable for passing to setOptions
    • setAdditionalMeasures

      public void setAdditionalMeasures(String[] additionalMeasures)
      Set a list of method names for additional measures to look for in Classifiers. This could contain many measures (of which only a subset may be produceable by the current Classifier) if an experiment is the type that iterates over a set of properties.
      指定者:
      setAdditionalMeasures 在接口中 SplitEvaluator
      参数:
      additionalMeasures - a list of method names
    • enumerateMeasures

      public Enumeration enumerateMeasures()
      Returns an enumeration of any additional measure names that might be in the classifier
      指定者:
      enumerateMeasures 在接口中 AdditionalMeasureProducer
      返回:
      an enumeration of the measure names
    • getMeasure

      public double getMeasure(String additionalMeasureName)
      Returns the value of the named measure
      指定者:
      getMeasure 在接口中 AdditionalMeasureProducer
      参数:
      additionalMeasureName - the name of the measure to query for its value
      返回:
      the value of the named measure
      抛出:
      IllegalArgumentException - if the named measure is not supported
    • getKeyTypes

      public Object[] getKeyTypes()
      Gets the data types of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.
      指定者:
      getKeyTypes 在接口中 SplitEvaluator
      返回:
      an array containing objects of the type of each key column. The objects should be Strings, or Doubles.
    • getKeyNames

      public String[] getKeyNames()
      Gets the names of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.
      指定者:
      getKeyNames 在接口中 SplitEvaluator
      返回:
      an array containing the name of each key column
    • getKey

      public Object[] getKey()
      Gets the key describing the current SplitEvaluator. For example This may contain the name of the classifier used for classifier predictive evaluation. The number of key fields must be constant for a given SplitEvaluator.
      指定者:
      getKey 在接口中 SplitEvaluator
      返回:
      an array of objects containing the key.
    • getResultTypes

      public Object[] getResultTypes()
      Gets the data types of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.
      指定者:
      getResultTypes 在接口中 SplitEvaluator
      返回:
      an array containing objects of the type of each result column. The objects should be Strings, or Doubles.
    • getResultNames

      public String[] getResultNames()
      Gets the names of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.
      指定者:
      getResultNames 在接口中 SplitEvaluator
      返回:
      an array containing the name of each result column
    • getResult

      public Object[] getResult(Instances train, Instances test) throws Exception
      Gets the results for the supplied train and test datasets. Now performs a deep copy of the classifier before it is built and evaluated (just in case the classifier is not initialized properly in buildClassifier()).
      指定者:
      getResult 在接口中 SplitEvaluator
      参数:
      train - the training Instances.
      test - the testing Instances.
      返回:
      the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).
      抛出:
      Exception - if a problem occurs while getting the results
    • classifierTipText

      public String classifierTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getClassifier

      public Classifier getClassifier()
      Get the value of Classifier.
      返回:
      Value of Classifier.
    • setClassifier

      public void setClassifier(Classifier newClassifier)
      Sets the classifier.
      参数:
      newClassifier - the new classifier to use.
    • getClassForIRStatistics

      public int getClassForIRStatistics()
      Get the value of ClassForIRStatistics.
      返回:
      Value of ClassForIRStatistics.
    • setClassForIRStatistics

      public void setClassForIRStatistics(int v)
      Set the value of ClassForIRStatistics.
      参数:
      v - Value to assign to ClassForIRStatistics.
    • getAttributeID

      public int getAttributeID()
      Get the index of Attibute Identifying the instances
      返回:
      index of outputed Attribute.
    • setAttributeID

      public void setAttributeID(int v)
      Set the index of Attibute Identifying the instances
      参数:
      v - index the attribute to output
    • getPredTargetColumn

      public boolean getPredTargetColumn()
      返回:
      true if the prediction and target columns must be outputed.
    • setPredTargetColumn

      public void setPredTargetColumn(boolean v)
      Set the flag for prediction and target output.
      参数:
      v - true if the 2 columns have to be outputed. false otherwise.
    • setClassifierName

      public void setClassifierName(String newClassifierName) throws Exception
      Set the Classifier to use, given it's class name. A new classifier will be instantiated.
      参数:
      newClassifierName - the Classifier class name.
      抛出:
      Exception - if the class name is invalid.
    • getRawResultOutput

      public String getRawResultOutput()
      Gets the raw output from the classifier
      指定者:
      getRawResultOutput 在接口中 SplitEvaluator
      返回:
      the raw output from th,0e classifier
    • toString

      public String toString()
      Returns a text description of the split evaluator.
      覆盖:
      toString 在类中 Object
      返回:
      a text description of the split evaluator.
    • getRevision

      public String getRevision()
      Returns the revision string.
      指定者:
      getRevision 在接口中 RevisionHandler
      返回:
      the revision