Experiment

java.lang.Object
- weka.experiment.Experiment

All Implemented Interfaces:: java.io.Serializable, OptionHandler, RevisionHandler

Direct Known Subclasses:: RemoteExperiment

public class Experiment
extends java.lang.Object
implements java.io.Serializable, OptionHandler, RevisionHandler

Holds all the necessary configuration information for a standard type experiment. This object is able to be serialized for storage on disk. Valid options are:

 -L <num>
  The lower run number to start the experiment from.
  (default 1)

 -U <num>
  The upper run number to end the experiment at (inclusive).
  (default 10)

 -T <arff file>
  The dataset to run the experiment on.
  (required, may be specified multiple times)

 -P <class name>
  The full class name of a ResultProducer (required).
  eg: weka.experiment.RandomSplitResultProducer

 -D <class name>
  The full class name of a ResultListener (required).
  eg: weka.experiment.CSVResultListener

 -N <string>
  A string containing any notes about the experiment.
  (default none)

 Options specific to result producer weka.experiment.RandomSplitResultProducer:

 -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 result producer.

Version:: $Revision: 13477 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

static java.lang.String FILE_EXTENSION
The filename extension that should be used for experiment files

Fields
Modifier and Type	Field and Description
`static java.lang.String`	`FILE_EXTENSION` The filename extension that should be used for experiment files

Constructor Summary

Constructors
Constructor and Description

Experiment()

Constructors
Constructor and Description
`Experiment()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`advanceCounters()` Increments iteration counters appropriately.
`void`	`classFirst(boolean flag)` Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
`boolean`	`getAdvanceDataSetFirst()` Get the value of m_DataSetFirstFirst.
`int`	`getCurrentDatasetNumber()` When an experiment is running, this returns the current dataset number.
`int`	`getCurrentPropertyNumber()` When an experiment is running, this returns the index of the current custom property value.
`int`	`getCurrentRunNumber()` When an experiment is running, this returns the current run number.
`javax.swing.DefaultListModel`	`getDatasets()` Gets the datasets in the experiment.
`java.lang.String`	`getNotes()` Get the user notes.
`java.lang.String[]`	`getOptions()` Gets the current settings of the experiment iterator.
`java.lang.Object`	`getPropertyArray()` Gets the array of values to set the custom property to.
`int`	`getPropertyArrayLength()` Gets the number of custom iterator values that have been defined for the experiment.
`java.lang.Object`	`getPropertyArrayValue(int index)` Gets a specified value from the custom property iterator array.
`PropertyNode[]`	`getPropertyPath()` Gets the path of properties taken to get to the custom property to iterate over.
`ResultListener`	`getResultListener()` Gets the result listener where results will be sent.
`ResultProducer`	`getResultProducer()` Get the result producer used for the current experiment.
`java.lang.String`	`getRevision()` Returns the revision string.
`int`	`getRunLower()` Get the lower run number for the experiment.
`int`	`getRunUpper()` Get the upper run number for the experiment.
`boolean`	`getUsePropertyIterator()` Gets whether the custom property iterator should be used.
`boolean`	`hasMoreIterations()` Returns true if there are more iterations to carry out in the experiment.
`void`	`initialize()` Prepares an experiment for running, initializing current iterator settings.
`java.util.Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options..
`static void`	`main(java.lang.String[] args)` Configures/Runs the Experiment from the command line.
`void`	`nextIteration()` Carries out the next iteration of the experiment.
`void`	`postProcess()` Signals that the experiment is finished running, so that cleanup can be done.
`static Experiment`	`read(java.lang.String filename)` Loads an experiment from a file.
`void`	`runExperiment()` Runs all iterations of the experiment, continuing past errors.
`void`	`runExperiment(boolean verbose)`
`void`	`setAdvanceDataSetFirst(boolean newAdvanceDataSetFirst)` Set the value of m_AdvanceDataSetFirst.
`void`	`setDatasets(javax.swing.DefaultListModel ds)` Set the datasets to use in the experiment
`void`	`setNotes(java.lang.String newNotes)` Set the user notes.
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setPropertyArray(java.lang.Object newPropArray)` Sets the array of values to set the custom property to.
`void`	`setPropertyPath(PropertyNode[] newPropertyPath)` Sets the path of properties taken to get to the custom property to iterate over.
`void`	`setResultListener(ResultListener newResultListener)` Sets the result listener where results will be sent.
`void`	`setResultProducer(ResultProducer newResultProducer)` Set the result producer used for the current experiment.
`void`	`setRunLower(int newRunLower)` Set the lower run number for the experiment.
`void`	`setRunUpper(int newRunUpper)` Set the upper run number for the experiment.
`void`	`setUsePropertyIterator(boolean newUsePropertyIterator)` Sets whether the custom property iterator should be used.
`java.lang.String`	`toString()` Gets a string representation of the experiment configuration.
`static void`	`write(java.lang.String filename, Experiment exp)` Writes the experiment to disk.

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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Field Detail
  - FILE_EXTENSION
```
public static java.lang.String FILE_EXTENSION
```
    The filename extension that should be used for experiment files
- Constructor Detail
  - Experiment
```
public Experiment()
```
- Method Detail
  - classFirst
```
public void classFirst(boolean flag)
```
    Sets whether the first attribute is treated as the class for all datasets involved in the experiment. This information is not output with the result of the experiments!
    
    Parameters:
    
    flag - whether the class attribute is the first and not the last
  - getAdvanceDataSetFirst
```
public boolean getAdvanceDataSetFirst()
```
    Get the value of m_DataSetFirstFirst.
    
    Returns:
    
    Value of m_DataSetFirstFirst.
  - setAdvanceDataSetFirst
```
public void setAdvanceDataSetFirst(boolean newAdvanceDataSetFirst)
```
    Set the value of m_AdvanceDataSetFirst.
    
    Parameters:
    
    newAdvanceDataSetFirst - Value to assign to m_AdvanceRunFirst.
  - getUsePropertyIterator
```
public boolean getUsePropertyIterator()
```
    Gets whether the custom property iterator should be used.
    
    Returns:
    
    true if so
  - setUsePropertyIterator
```
public void setUsePropertyIterator(boolean newUsePropertyIterator)
```
    Sets whether the custom property iterator should be used.
    
    Parameters:
    
    newUsePropertyIterator - true if so
  - getPropertyPath
```
public PropertyNode[] getPropertyPath()
```
    Gets the path of properties taken to get to the custom property to iterate over.
    
    Returns:
    
    an array of PropertyNodes
  - setPropertyPath
```
public void setPropertyPath(PropertyNode[] newPropertyPath)
```
    Sets the path of properties taken to get to the custom property to iterate over.
    
    Parameters:
    
    newPropertyPath - an array of PropertyNodes
  - setPropertyArray
```
public void setPropertyArray(java.lang.Object newPropArray)
```
    Sets the array of values to set the custom property to.
    
    Parameters:
    
    newPropArray - a value of type Object which should be an array of the appropriate values.
  - getPropertyArray
```
public java.lang.Object getPropertyArray()
```
    Gets the array of values to set the custom property to.
    
    Returns:
    
    a value of type Object which should be an array of the appropriate values.
  - getPropertyArrayLength
```
public int getPropertyArrayLength()
```
    Gets the number of custom iterator values that have been defined for the experiment.
    
    Returns:
    
    the number of custom property iterator values.
  - getPropertyArrayValue
```
public java.lang.Object getPropertyArrayValue(int index)
```
    Gets a specified value from the custom property iterator array.
    
    Parameters:
    
    index - the index of the value wanted
    
    Returns:
    
    the property array value
  - getCurrentRunNumber
```
public int getCurrentRunNumber()
```
    When an experiment is running, this returns the current run number.
    
    Returns:
    
    the current run number.
  - getCurrentDatasetNumber
```
public int getCurrentDatasetNumber()
```
    When an experiment is running, this returns the current dataset number.
    
    Returns:
    
    the current dataset number.
  - getCurrentPropertyNumber
```
public int getCurrentPropertyNumber()
```
    When an experiment is running, this returns the index of the current custom property value.
    
    Returns:
    
    the index of the current custom property value.
  - initialize
```
public void initialize()
                throws java.lang.Exception
```
    Prepares an experiment for running, initializing current iterator settings.
    
    Throws:
    
    java.lang.Exception - if an error occurs
  - hasMoreIterations
```
public boolean hasMoreIterations()
```
    Returns true if there are more iterations to carry out in the experiment.
    
    Returns:
    
    true if so
  - nextIteration
```
public void nextIteration()
                   throws java.lang.Exception
```
    Carries out the next iteration of the experiment.
    
    Throws:
    
    java.lang.Exception - if an error occurs
  - advanceCounters
```
public void advanceCounters()
```
    Increments iteration counters appropriately.
  - runExperiment
```
public void runExperiment(boolean verbose)
```
  - runExperiment
```
public void runExperiment()
```
    Runs all iterations of the experiment, continuing past errors.
  - postProcess
```
public void postProcess()
                 throws java.lang.Exception
```
    Signals that the experiment is finished running, so that cleanup can be done.
    
    Throws:
    
    java.lang.Exception - if an error occurs
  - getDatasets
```
public javax.swing.DefaultListModel getDatasets()
```
    Gets the datasets in the experiment.
    
    Returns:
    
    the datasets in the experiment.
  - setDatasets
```
public void setDatasets(javax.swing.DefaultListModel ds)
```
    Set the datasets to use in the experiment
    
    Parameters:
    
    ds - the list of datasets to use
  - getResultListener
```
public ResultListener getResultListener()
```
    Gets the result listener where results will be sent.
    
    Returns:
    
    the result listener where results will be sent.
  - setResultListener
```
public void setResultListener(ResultListener newResultListener)
```
    Sets the result listener where results will be sent.
    
    Parameters:
    
    newResultListener - the result listener where results will be sent.
  - getResultProducer
```
public ResultProducer getResultProducer()
```
    Get the result producer used for the current experiment.
    
    Returns:
    
    the result producer used for the current experiment.
  - setResultProducer
```
public void setResultProducer(ResultProducer newResultProducer)
```
    Set the result producer used for the current experiment.
    
    Parameters:
    
    newResultProducer - result producer to use for the current experiment.
  - getRunUpper
```
public int getRunUpper()
```
    Get the upper run number for the experiment.
    
    Returns:
    
    the upper run number for the experiment.
  - setRunUpper
```
public void setRunUpper(int newRunUpper)
```
    Set the upper run number for the experiment.
    
    Parameters:
    
    newRunUpper - the upper run number for the experiment.
  - getRunLower
```
public int getRunLower()
```
    Get the lower run number for the experiment.
    
    Returns:
    
    the lower run number for the experiment.
  - setRunLower
```
public void setRunLower(int newRunLower)
```
    Set the lower run number for the experiment.
    
    Parameters:
    
    newRunLower - the lower run number for the experiment.
  - getNotes
```
public java.lang.String getNotes()
```
    Get the user notes.
    
    Returns:
    
    User notes associated with the experiment.
  - setNotes
```
public void setNotes(java.lang.String newNotes)
```
    Set the user notes.
    
    Parameters:
    
    newNotes - New user notes.
  - listOptions
```
public java.util.Enumeration<Option> 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(java.lang.String[] options)
                throws java.lang.Exception
```
    Parses a given list of options.
    Valid options are:
```
 -L <num>
  The lower run number to start the experiment from.
  (default 1)
 
```
```
 -U <num>
  The upper run number to end the experiment at (inclusive).
  (default 10)
 
```
```
 -T <arff file>
  The dataset to run the experiment on.
  (required, may be specified multiple times)
 
```
```
 -P <class name>
  The full class name of a ResultProducer (required).
  eg: weka.experiment.RandomSplitResultProducer
 
```
```
 -D <class name>
  The full class name of a ResultListener (required).
  eg: weka.experiment.CSVResultListener
 
```
```
 -N <string>
  A string containing any notes about the experiment.
  (default none)
 
```
```
 Options specific to result producer weka.experiment.RandomSplitResultProducer:
 
```
```
 -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 result producer.
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings of the experiment iterator.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - toString
```
public java.lang.String toString()
```
    Gets a string representation of the experiment configuration.
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a value of type 'String'
  - read
```
public static Experiment read(java.lang.String filename)
                       throws java.lang.Exception
```
    Loads an experiment from a file.
    
    Parameters:
    
    filename - the file to load the experiment from
    
    Returns:
    
    the experiment
    
    Throws:
    
    java.lang.Exception - if loading fails
  - write
```
public static void write(java.lang.String filename,
                         Experiment exp)
                  throws java.lang.Exception
```
    Writes the experiment to disk.
    
    Parameters:
    
    filename - the file to write to
    
    exp - the experiment to save
    
    Throws:
    
    java.lang.Exception - if writing fails
  - main
```
public static void main(java.lang.String[] args)
```
    Configures/Runs the Experiment from the command line.
    
    Parameters:
    
    args - command line arguments to the Experiment.
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Returns:
    
    the revision

Class Experiment

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Field Detail

FILE_EXTENSION

Constructor Detail

Experiment

Method Detail

classFirst

getAdvanceDataSetFirst

setAdvanceDataSetFirst

getUsePropertyIterator

setUsePropertyIterator

getPropertyPath

setPropertyPath

setPropertyArray

getPropertyArray

getPropertyArrayLength

getPropertyArrayValue

getCurrentRunNumber

getCurrentDatasetNumber

getCurrentPropertyNumber

initialize

hasMoreIterations

nextIteration

advanceCounters

runExperiment

runExperiment

postProcess

getDatasets

setDatasets

getResultListener

setResultListener

getResultProducer

setResultProducer

getRunUpper

setRunUpper

getRunLower

setRunLower

getNotes

setNotes

listOptions

setOptions

getOptions

toString

read

write

main

getRevision