RandomSplitResultProducer (weka-dev 3.7.6-SNAPSHOT API)

java.lang.Object
- weka.experiment.RandomSplitResultProducer

All Implemented Interfaces:: Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, ResultProducer

public class RandomSplitResultProducer
extends Object
implements ResultProducer, OptionHandler, AdditionalMeasureProducer, RevisionHandler

Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.

Valid options are:

 -P <percent>
  The percentage of instances to use for training.
  (default 66)

 -D
 Save raw split evaluator output.

 -O <file/directory name/path>
  The filename where raw output will be stored.
  If a directory name is specified then then individual
  outputs will be gzipped, otherwise all output will be
  zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)

 -W <class name>
  The full class name of a SplitEvaluator.
  eg: weka.experiment.ClassifierSplitEvaluator

 -R
  Set when data is not to be randomized and the data sets' size.
  Is not to be determined via probabilistic rounding.

 
 Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:

 -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 split evaluator.

Version:: $Revision: 8034 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static String`	`DATASET_FIELD_NAME` The name of the key field containing the dataset name
`static String`	`RUN_FIELD_NAME` The name of the key field containing the run number
`static String`	`TIMESTAMP_FIELD_NAME` The name of the result field containing the timestamp

Constructor Summary

Constructors
Constructor and Description

RandomSplitResultProducer()

Constructors
Constructor and Description
`RandomSplitResultProducer()`

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`doRun(int run)` Gets the results for a specified run number.
`void`	`doRunKeys(int run)` Gets the keys for a specified run number.
`Enumeration`	`enumerateMeasures()` Returns an enumeration of any additional measure names that might be in the SplitEvaluator
`String`	`getCompatibilityState()` Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
`String[]`	`getKeyNames()` Gets the names of each of the columns produced for a single run.
`Object[]`	`getKeyTypes()` Gets the data types of each of the columns produced for a single run.
`double`	`getMeasure(String additionalMeasureName)` Returns the value of the named measure
`String[]`	`getOptions()` Gets the current settings of the result producer.
`File`	`getOutputFile()` Get the value of OutputFile.
`boolean`	`getRandomizeData()` Get if dataset is to be randomized
`boolean`	`getRawOutput()` Get if raw split evaluator output is to be saved
`String[]`	`getResultNames()` Gets the names of each of the columns produced for a single run.
`Object[]`	`getResultTypes()` Gets the data types of each of the columns produced for a single run.
`String`	`getRevision()` Returns the revision string.
`SplitEvaluator`	`getSplitEvaluator()` Get the SplitEvaluator.
`static Double`	`getTimestamp()` Gets a Double representing the current date and time.
`double`	`getTrainPercent()` Get the value of TrainPercent.
`String`	`globalInfo()` Returns a string describing this result producer
`Enumeration`	`listOptions()` Returns an enumeration describing the available options..
`String`	`outputFileTipText()` Returns the tip text for this property
`void`	`postProcess()` Perform any postprocessing.
`void`	`preProcess()` Prepare to generate results.
`String`	`randomizeDataTipText()` Returns the tip text for this property
`String`	`rawOutputTipText()` Returns the tip text for this property
`void`	`setAdditionalMeasures(String[] additionalMeasures)` Set a list of method names for additional measures to look for in SplitEvaluators.
`void`	`setInstances(Instances instances)` Sets the dataset that results will be obtained for.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setOutputFile(File newOutputFile)` Set the value of OutputFile.
`void`	`setRandomizeData(boolean d)` Set to true if dataset is to be randomized
`void`	`setRawOutput(boolean d)` Set to true if raw split evaluator output is to be saved
`void`	`setResultListener(ResultListener listener)` Sets the object to send results of each run to.
`void`	`setSplitEvaluator(SplitEvaluator newSplitEvaluator)` Set the SplitEvaluator.
`void`	`setTrainPercent(double newTrainPercent)` Set the value of TrainPercent.
`String`	`splitEvaluatorTipText()` Returns the tip text for this property
`String`	`toString()` Gets a text descrption of the result producer.
`String`	`trainPercentTipText()` Returns the tip text for this property

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - DATASET_FIELD_NAME
```
public static String DATASET_FIELD_NAME
```
    The name of the key field containing the dataset name
  - RUN_FIELD_NAME
```
public static String RUN_FIELD_NAME
```
    The name of the key field containing the run number
  - TIMESTAMP_FIELD_NAME
```
public static String TIMESTAMP_FIELD_NAME
```
    The name of the result field containing the timestamp
- Constructor Detail
  - RandomSplitResultProducer
```
public RandomSplitResultProducer()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this result producer
    
    Returns:
    a description of the result producer suitable for displaying in the explorer/experimenter gui
  - setInstances
```
public void setInstances(Instances instances)
```
    Sets the dataset that results will be obtained for.
    
    Specified by:
    
    setInstances in interface ResultProducer
    
    Parameters:
    instances - a value of type 'Instances'.
  - setAdditionalMeasures
```
public void setAdditionalMeasures(String[] additionalMeasures)
```
    Set a list of method names for additional measures to look for in SplitEvaluators. This could contain many measures (of which only a subset may be produceable by the current SplitEvaluator) if an experiment is the type that iterates over a set of properties.
    
    Specified by:
    
    setAdditionalMeasures in interface ResultProducer
    
    Parameters:
    additionalMeasures - an array of measure names, null if none
  - enumerateMeasures
```
public Enumeration enumerateMeasures()
```
    Returns an enumeration of any additional measure names that might be in the SplitEvaluator
    
    Specified by:
    
    enumerateMeasures in interface AdditionalMeasureProducer
    
    Returns:
    an enumeration of the measure names
  - getMeasure
```
public double getMeasure(String additionalMeasureName)
```
    Returns the value of the named measure
    
    Specified by:
    
    getMeasure in interface AdditionalMeasureProducer
    
    Parameters:
    additionalMeasureName - the name of the measure to query for its value
    
    Returns:
    the value of the named measure
    
    Throws:
    
    IllegalArgumentException - if the named measure is not supported
  - setResultListener
```
public void setResultListener(ResultListener listener)
```
    Sets the object to send results of each run to.
    
    Specified by:
    
    setResultListener in interface ResultProducer
    
    Parameters:
    listener - a value of type 'ResultListener'
  - getTimestamp
```
public static Double getTimestamp()
```
    Gets a Double representing the current date and time. eg: 1:46pm on 20/5/1999 -> 19990520.1346
    
    Returns:
    a value of type Double
  - preProcess
```
public void preProcess()
                throws Exception
```
    Prepare to generate results.
    
    Specified by:
    
    preProcess in interface ResultProducer
    
    Throws:
    
    Exception - if an error occurs during preprocessing.
  - postProcess
```
public void postProcess()
                 throws Exception
```
    Perform any postprocessing. When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
    
    Specified by:
    
    postProcess in interface ResultProducer
    
    Throws:
    
    Exception - if an error occurs
  - doRunKeys
```
public void doRunKeys(int run)
               throws Exception
```
    Gets the keys for a specified run number. Different run numbers correspond to different randomizations of the data. Keys produced should be sent to the current ResultListener
    
    Specified by:
    
    doRunKeys in interface ResultProducer
    
    Parameters:
    run - the run number to get keys for.
    
    Throws:
    
    Exception - if a problem occurs while getting the keys
  - doRun
```
public void doRun(int run)
           throws Exception
```
    Gets the results for a specified run number. Different run numbers correspond to different randomizations of the data. Results produced should be sent to the current ResultListener
    
    Specified by:
    
    doRun in interface ResultProducer
    
    Parameters:
    run - the run number to get results for.
    
    Throws:
    
    Exception - if a problem occurs while getting the results
  - getKeyNames
```
public String[] getKeyNames()
```
    Gets the names of each of the columns produced for a single run. This method should really be static.
    
    Specified by:
    
    getKeyNames in interface ResultProducer
    
    Returns:
    an array containing the name of each column
  - getKeyTypes
```
public Object[] getKeyTypes()
```
    Gets the data types of each of the columns produced for a single run. This method should really be static.
    
    Specified by:
    
    getKeyTypes in interface ResultProducer
    
    Returns:
    an array containing objects of the type of each column. The objects should be Strings, or Doubles.
  - getResultNames
```
public String[] getResultNames()
```
    Gets the names of each of the columns produced for a single run. This method should really be static.
    
    Specified by:
    
    getResultNames in interface ResultProducer
    
    Returns:
    an array containing the name of each column
  - getResultTypes
```
public Object[] getResultTypes()
```
    Gets the data types of each of the columns produced for a single run. This method should really be static.
    
    Specified by:
    
    getResultTypes in interface ResultProducer
    
    Returns:
    an array containing objects of the type of each column. The objects should be Strings, or Doubles.
  - getCompatibilityState
```
public String getCompatibilityState()
```
    Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface). For example, a cross-validation ResultProducer may have a setting for the number of folds. For a given state, the results produced should be compatible. Typically if a ResultProducer is an OptionHandler, this string will represent the command line arguments required to set the ResultProducer to that state.
    
    Specified by:
    
    getCompatibilityState in interface ResultProducer
    
    Returns:
    the description of the ResultProducer state, or null if no state is defined
  - outputFileTipText
```
public String outputFileTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getOutputFile
```
public File getOutputFile()
```
    Get the value of OutputFile.
    
    Returns:
    Value of OutputFile.
  - setOutputFile
```
public void setOutputFile(File newOutputFile)
```
    Set the value of OutputFile.
    
    Parameters:
    newOutputFile - Value to assign to OutputFile.
  - randomizeDataTipText
```
public String randomizeDataTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getRandomizeData
```
public boolean getRandomizeData()
```
    Get if dataset is to be randomized
    
    Returns:
    true if dataset is to be randomized
  - setRandomizeData
```
public void setRandomizeData(boolean d)
```
    Set to true if dataset is to be randomized
    
    Parameters:
    d - true if dataset is to be randomized
  - rawOutputTipText
```
public String rawOutputTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getRawOutput
```
public boolean getRawOutput()
```
    Get if raw split evaluator output is to be saved
    
    Returns:
    true if raw split evalutor output is to be saved
  - setRawOutput
```
public void setRawOutput(boolean d)
```
    Set to true if raw split evaluator output is to be saved
    
    Parameters:
    d - true if output is to be saved
  - trainPercentTipText
```
public String trainPercentTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getTrainPercent
```
public double getTrainPercent()
```
    Get the value of TrainPercent.
    
    Returns:
    Value of TrainPercent.
  - setTrainPercent
```
public void setTrainPercent(double newTrainPercent)
```
    Set the value of TrainPercent.
    
    Parameters:
    newTrainPercent - Value to assign to TrainPercent.
  - splitEvaluatorTipText
```
public String splitEvaluatorTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getSplitEvaluator
```
public SplitEvaluator getSplitEvaluator()
```
    Get the SplitEvaluator.
    
    Returns:
    the SplitEvaluator.
  - setSplitEvaluator
```
public void setSplitEvaluator(SplitEvaluator newSplitEvaluator)
```
    Set the SplitEvaluator.
    
    Parameters:
    newSplitEvaluator - new SplitEvaluator to use.
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options..
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options.
    Valid options are:
```
 -P <percent>
  The percentage of instances to use for training.
  (default 66)
```
```
 -D
 Save raw split evaluator output.
```
```
 -O <file/directory name/path>
  The filename where raw output will be stored.
  If a directory name is specified then then individual
  outputs will be gzipped, otherwise all output will be
  zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)
```
```
 -W <class name>
  The full class name of a SplitEvaluator.
  eg: weka.experiment.ClassifierSplitEvaluator
```
```
 -R
  Set when data is not to be randomized and the data sets' size.
  Is not to be determined via probabilistic rounding.
```
```
 
 Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:
 
```
```
 -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 split evaluator.
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the result producer.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    an array of strings suitable for passing to setOptions
  - toString
```
public String toString()
```
    Gets a text descrption of the result producer.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a text description of the result producer.
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Returns:
    the revision

Class RandomSplitResultProducer

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

DATASET_FIELD_NAME

RUN_FIELD_NAME

TIMESTAMP_FIELD_NAME

Constructor Detail

RandomSplitResultProducer

Method Detail

globalInfo

setInstances

setAdditionalMeasures

enumerateMeasures

getMeasure

setResultListener

getTimestamp

preProcess

postProcess

doRunKeys

doRun

getKeyNames

getKeyTypes

getResultNames

getResultTypes

getCompatibilityState

outputFileTipText

getOutputFile

setOutputFile

randomizeDataTipText

getRandomizeData

setRandomizeData

rawOutputTipText

getRawOutput

setRawOutput

trainPercentTipText

getTrainPercent

setTrainPercent

splitEvaluatorTipText

getSplitEvaluator

setSplitEvaluator

listOptions

setOptions

getOptions

toString

getRevision