MultiScheme

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.MultipleClassifiersCombiner
  - - weka.classifiers.RandomizableMultipleClassifiersCombiner
    - - weka.classifiers.meta.MultiScheme

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler

public class MultiScheme
extends RandomizableMultipleClassifiersCombiner

Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data. Performance is measured based on percent correct (classification) or mean-squared error (regression).

Valid options are:

 -X <number of folds>
  Use cross validation for model selection using the
  given number of folds. (default 0, is to
  use training error)

 -S <num>
  Random number seed.
  (default 1)

 -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Version:: $Revision: 1.25 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

MultiScheme()

Constructors
Constructor and Description
`MultiScheme()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances data)` Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
`java.lang.String`	`classifiersTipText()` Returns the tip text for this property
`java.lang.String`	`debugTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Returns class probabilities.
`int`	`getBestClassifierIndex()` Get the index of the classifier that was determined as best during cross-validation.
`Classifier`	`getClassifier(int index)` Gets a single classifier from the set of available classifiers.
`Classifier[]`	`getClassifiers()` Gets the list of possible classifers to choose from.
`boolean`	`getDebug()` Get whether debugging is turned on
`int`	`getNumFolds()` Gets the number of folds for cross-validation.
`java.lang.String[]`	`getOptions()` Gets the current settings of the Classifier.
`java.lang.String`	`getRevision()` Returns the revision string.
`int`	`getSeed()` Gets the random number seed.
`java.lang.String`	`globalInfo()` Returns a string describing classifier
`java.util.Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String`	`numFoldsTipText()` Returns the tip text for this property
`java.lang.String`	`seedTipText()` Returns the tip text for this property
`void`	`setClassifiers(Classifier[] classifiers)` Sets the list of possible classifers to choose from.
`void`	`setDebug(boolean debug)` Set debugging mode
`void`	`setNumFolds(int numFolds)` Sets the number of folds for cross-validation.
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setSeed(int seed)` Sets the seed for random number generation.
`java.lang.String`	`toString()` Output a representation of this classifier

Methods inherited from class weka.classifiers.MultipleClassifiersCombiner
getCapabilities

Methods inherited from class weka.classifiers.Classifier
classifyInstance, forName, makeCopies, makeCopy

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

- Constructor Detail
  - MultiScheme
```
public MultiScheme()
```
- Method Detail
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    
    a description suitable for displaying in the explorer/experimenter gui
  - listOptions
```
public java.util.Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class RandomizableMultipleClassifiersCombiner
    
    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:
```
 -X <number of folds>
  Use cross validation for model selection using the
  given number of folds. (default 0, is to
  use training error)
```
```
 -S <num>
  Random number seed.
  (default 1)
```
```
 -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
```
```
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class RandomizableMultipleClassifiersCombiner
    
    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 Classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class RandomizableMultipleClassifiersCombiner
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - classifiersTipText
```
public java.lang.String classifiersTipText()
```
    Returns the tip text for this property
    
    Overrides:
    
    classifiersTipText in class MultipleClassifiersCombiner
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setClassifiers
```
public void setClassifiers(Classifier[] classifiers)
```
    Sets the list of possible classifers to choose from.
    
    Overrides:
    
    setClassifiers in class MultipleClassifiersCombiner
    
    Parameters:
    
    classifiers - an array of classifiers with all options set.
  - getClassifiers
```
public Classifier[] getClassifiers()
```
    Gets the list of possible classifers to choose from.
    
    Overrides:
    
    getClassifiers in class MultipleClassifiersCombiner
    
    Returns:
    
    the array of Classifiers
  - getClassifier
```
public Classifier getClassifier(int index)
```
    Gets a single classifier from the set of available classifiers.
    
    Overrides:
    
    getClassifier in class MultipleClassifiersCombiner
    
    Parameters:
    
    index - the index of the classifier wanted
    
    Returns:
    
    the Classifier
  - seedTipText
```
public java.lang.String seedTipText()
```
    Returns the tip text for this property
    
    Overrides:
    
    seedTipText in class RandomizableMultipleClassifiersCombiner
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setSeed
```
public void setSeed(int seed)
```
    Sets the seed for random number generation.
    
    Specified by:
    
    setSeed in interface Randomizable
    
    Overrides:
    
    setSeed in class RandomizableMultipleClassifiersCombiner
    
    Parameters:
    
    seed - the random number seed
  - getSeed
```
public int getSeed()
```
    Gets the random number seed.
    
    Specified by:
    
    getSeed in interface Randomizable
    
    Overrides:
    
    getSeed in class RandomizableMultipleClassifiersCombiner
    
    Returns:
    
    the random number seed
  - numFoldsTipText
```
public java.lang.String numFoldsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getNumFolds
```
public int getNumFolds()
```
    Gets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.
    
    Returns:
    
    the number of folds for cross-validation
  - setNumFolds
```
public void setNumFolds(int numFolds)
```
    Sets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.
    
    Parameters:
    
    numFolds - the number of folds for cross-validation
  - debugTipText
```
public java.lang.String debugTipText()
```
    Returns the tip text for this property
    
    Overrides:
    
    debugTipText in class Classifier
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDebug
```
public void setDebug(boolean debug)
```
    Set debugging mode
    
    Overrides:
    
    setDebug in class Classifier
    
    Parameters:
    
    debug - true if debug output should be printed
  - getDebug
```
public boolean getDebug()
```
    Get whether debugging is turned on
    
    Overrides:
    
    getDebug in class Classifier
    
    Returns:
    
    true if debugging output is on
  - getBestClassifierIndex
```
public int getBestClassifierIndex()
```
    Get the index of the classifier that was determined as best during cross-validation.
    
    Returns:
    
    the index in the classifier array
  - buildClassifier
```
public void buildClassifier(Instances data)
                     throws java.lang.Exception
```
    Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    
    data - the training data to be used for generating the boosted classifier.
    
    Throws:
    
    java.lang.Exception - if the classifier could not be built successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception
```
    Returns class probabilities.
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    
    instance - the instance to be classified
    
    Returns:
    
    the distribution for the instance
    
    Throws:
    
    java.lang.Exception - if instance could not be classified successfully
  - toString
```
public java.lang.String toString()
```
    Output a representation of this classifier
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a string representation of the classifier
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Classifier
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain the following arguments: -t training file [-T test file] [-c class index]

Class MultiScheme

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Constructor Detail

MultiScheme

Method Detail

globalInfo

listOptions

setOptions

getOptions

classifiersTipText

setClassifiers

getClassifiers

getClassifier

seedTipText

setSeed

getSeed

numFoldsTipText

getNumFolds

setNumFolds

debugTipText

setDebug

getDebug

getBestClassifierIndex

buildClassifier

distributionForInstance

toString

getRevision

main