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Class weka.experiment.RandomSplitResultProducer

java.lang.Object
   |
   +----weka.experiment.RandomSplitResultProducer

public class RandomSplitResultProducer

extends Object

implements ResultProducer, OptionHandler

Version:

$Revision: 1.2 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

DATASET_FIELD_NAME

RUN_FIELD_NAME

TIMESTAMP_FIELD_NAME

RandomSplitResultProducer()

doRun(int)

Gets the results for a specified run number.

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).

getKeyNames()

Gets the names of each of the columns produced for a single run.

getKeyTypes()

Gets the data types of each of the columns produced for a single run.

getOptions()

Gets the current settings of the result producer.

getResultNames()

Gets the names of each of the columns produced for a single run.

getResultTypes()

Gets the data types of each of the columns produced for a single run.

getSplitEvaluator()

Get the SplitEvaluator.

getTimestamp()

Gets a Double representing the current date and time.

getTrainPercent()

Get the value of TrainPercent.

listOptions()

Returns an enumeration describing the available options.

postProcess()

Perform any postprocessing.

preProcess()

Prepare to generate results.

setInstances(Instances)

Sets the dataset that results will be obtained for.

setOptions(String[])

Parses a given list of options.

setResultListener(ResultListener)

Sets the object to send results of each run to.

setSplitEvaluator(SplitEvaluator)

Set the SplitEvaluator.

setTrainPercent(int)

Set the value of TrainPercent.

toString()

Gets a text descrption of the result producer.

 public static String DATASET_FIELD_NAME

 public static String RUN_FIELD_NAME

 public static String TIMESTAMP_FIELD_NAME

 public RandomSplitResultProducer()

 public void setInstances(Instances instances)

Sets the dataset that results will be obtained for.

Parameters:

instances - a value of type 'Instances'.

 public void setResultListener(ResultListener listener)

Sets the object to send results of each run to.

Parameters:

listener - a value of type 'ResultListener'

 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

 public void preProcess() throws Exception

Prepare to generate results.

Throws: Exception

if an error occurs during preprocessing.

 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.

Throws: Exception

if an error occurs

 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

Parameters:

run - the run number to get results for.

Throws: Exception

if a problem occurs while getting the results

 public String[] getKeyNames()

Gets the names of each of the columns produced for a single run. This method should really be static.

Returns:

an array containing the name of each column

 public Object[] getKeyTypes()

Gets the data types of each of the columns produced for a single run. This method should really be static.

Returns:

an array containing objects of the type of each column. The objects should be Strings, or Doubles.

 public String[] getResultNames()

Gets the names of each of the columns produced for a single run. This method should really be static.

Returns:

an array containing the name of each column

 public Object[] getResultTypes()

Gets the data types of each of the columns produced for a single run. This method should really be static.

Returns:

an array containing objects of the type of each column. The objects should be Strings, or Doubles.

 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.

Returns:

the description of the ResultProducer state, or null if no state is defined

 public int getTrainPercent()

Get the value of TrainPercent.

Returns:

Value of TrainPercent.

 public void setTrainPercent(int newTrainPercent)

Set the value of TrainPercent.

Parameters:

newTrainPercent - Value to assign to TrainPercent.

 public SplitEvaluator getSplitEvaluator()

Get the SplitEvaluator.

Returns:

the SplitEvaluator.

 public void setSplitEvaluator(SplitEvaluator newSplitEvaluator)

Set the SplitEvaluator.

Parameters:

newSplitEvaluator - new SplitEvaluator to use.

 public Enumeration listOptions()

Returns an enumeration describing the available options.

Returns:

an enumeration of all the available options

 public void setOptions(String options[]) throws Exception

Parses a given list of options. Valid options are:

-P num
The percent of instances used for training.

-W classname
Specify the full class name of the split evaluator.

All option after -- will be passed to the split evaluator.

Parameters:

options - the list of options as an array of strings

Throws: Exception

if an option is not supported

 public String[] getOptions()

Gets the current settings of the result producer.

Returns:

an array of strings suitable for passing to setOptions

 public String toString()

Gets a text descrption of the result producer.

Returns:

a text description of the result producer.

Overrides:

toString in class Object

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