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Class weka.experiment.RegressionSplitEvaluator

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

public class RegressionSplitEvaluator

extends Object

implements SplitEvaluator, OptionHandler, AdditionalMeasureProducer

Author:

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

RegressionSplitEvaluator()

No args constructor.

classifierTipText()

Returns the tip text for this property

enumerateMeasures()

Returns an enumeration of any additional measure names that might be in the classifier

getClassifier()

Get the value of Classifier.

getKey()

Gets the key describing the current SplitEvaluator.

getKeyNames()

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

getKeyTypes()

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

getMeasure(String)

Returns the value of the named measure

getOptions()

Gets the current settings of the Classifier.

getRawResultOutput()

Gets the raw output from the classifier

getResult(Instances, Instances)

Gets the results for the supplied train and test datasets.

getResultNames()

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

getResultTypes()

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

globalInfo()

Returns a string describing this split evaluator

listOptions()

Returns an enumeration describing the available options.

setAdditionalMeasures(String[])

Set a list of method names for additional measures to look for in Classifiers.

setClassifier(Classifier)

Sets the classifier.

setClassifierName(String)

Set the Classifier to use, given it's class name.

setOptions(String[])

Parses a given list of options.

toString()

Returns a text description of the split evaluator.

 public RegressionSplitEvaluator()

No args constructor.

 public String globalInfo()

Returns a string describing this split evaluator

Returns:

a description of the split evaluator suitable for displaying in the explorer/experimenter gui

 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:

-W classname
Specify the full class name of the classifier to evaluate.

All option after -- will be passed to the classifier.

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 Classifier.

Returns:

an array of strings suitable for passing to setOptions

 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.

Parameters:

additionalMeasures - an array of method names.

 public Enumeration enumerateMeasures()

Returns an enumeration of any additional measure names that might be in the classifier

Returns:

an enumeration of the measure names

 public double getMeasure(String additionalMeasureName)

Returns the value of the named measure

Parameters:

measureName - 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

 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.

Returns:

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

 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.

Returns:

an array containing the name of each key column

 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.

Returns:

an array of objects containing the key.

 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.

Returns:

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

 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.

Returns:

an array containing the name of each result column

 public Object[] getResult(Instances train,
                           Instances test) throws Exception

Gets the results for the supplied train and test datasets.

Parameters:

train - the training Instances.

test - the testing Instances.

Returns:

the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).

Throws: Exception

if a problem occurs while getting the results

 public String classifierTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

 public Classifier getClassifier()

Get the value of Classifier.

Returns:

Value of Classifier.

 public void setClassifier(Classifier newClassifier)

Sets the classifier.

Parameters:

newClassifier - the new classifier to use.

 public void setClassifierName(String newClassifierName) throws Exception

Set the Classifier to use, given it's class name. A new classifier will be instantiated.

Parameters:

newClassifier - the Classifier class name.

Throws: Exception

if the class name is invalid.

 public String getRawResultOutput()

Gets the raw output from the classifier

Returns:

the raw output from the classifier

 public String toString()

Returns a text description of the split evaluator.

Returns:

a text description of the split evaluator.

Overrides:

toString in class Object

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