RandomSubSpace (weka-stable 3.6.14 API)

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.SingleClassifierEnhancer
  - - weka.classifiers.IteratedSingleClassifierEnhancer
    - - weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
      - weka.classifiers.meta.RandomSubSpace

All Implemented Interfaces:: Serializable, Cloneable, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class RandomSubSpace
extends RandomizableIteratedSingleClassifierEnhancer
implements WeightedInstancesHandler, TechnicalInformationHandler

This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity. The classifier consists of multiple trees constructed systematically by pseudorandomly selecting subsets of components of the feature vector, that is, trees constructed in randomly chosen subspaces.

For more information, see

Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.

BibTeX:

 @article{Ho1998,
    author = {Tin Kam Ho},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    number = {8},
    pages = {832-844},
    title = {The Random Subspace Method for Constructing Decision Forests},
    volume = {20},
    year = {1998},
    ISSN = {0162-8828},
    URL = {http://citeseer.ist.psu.edu/ho98random.html}
 }

Valid options are:

 -P
  Size of each subspace:
   < 1: percentage of the number of attributes
   >=1: absolute number of attributes

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

 -I <num>
  Number of iterations.
  (default 10)

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.REPTree)

 
 Options specific to classifier weka.classifiers.trees.REPTree:

 -M <minimum number of instances>
  Set minimum number of instances per leaf (default 2).

 -V <minimum variance for split>
  Set minimum numeric class variance proportion
  of train variance for split (default 1e-3).

 -N <number of folds>
  Number of folds for reduced error pruning (default 3).

 -S <seed>
  Seed for random data shuffling (default 1).

 -P
  No pruning.

 -L
  Maximum tree depth (default -1, no maximum)

Options after -- are passed to the designated classifier.

Version:: $Revision: 1.4 $
Author:: Bernhard Pfahringer (bernhard@cs.waikato.ac.nz), Peter Reutemann (fracpete@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

RandomSubSpace()
Constructor.

Constructors
Constructor and Description
`RandomSubSpace()` Constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances data)` builds the classifier.
`double[]`	`distributionForInstance(Instance instance)` Calculates the class membership probabilities for the given test instance.
`String[]`	`getOptions()` Gets the current settings of the Classifier.
`String`	`getRevision()` Returns the revision string.
`double`	`getSubSpaceSize()` Gets the size of each subSpace, as a percentage of the training set size.
`TechnicalInformation`	`getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`String`	`globalInfo()` Returns a string describing classifier
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] args)` Main method for testing this class.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setSubSpaceSize(double value)` Sets the size of each subSpace, as a percentage of the training set size.
`String`	`subSpaceSizeTipText()` Returns the tip text for this property
`String`	`toString()` Returns description of the bagged classifier.

Methods inherited from class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer
getNumIterations, numIterationsTipText, setNumIterations

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getCapabilities, getClassifier, setClassifier

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

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

- Constructor Detail
  - RandomSubSpace
```
public RandomSubSpace()
```
    Constructor.
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    
    a description suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public TechnicalInformation getTechnicalInformation()
```
    Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class RandomizableIteratedSingleClassifierEnhancer
    
    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
  Size of each subspace:
   < 1: percentage of the number of attributes
   >=1: absolute number of attributes
 
```
```
 -S <num>
  Random number seed.
  (default 1)
```
```
 -I <num>
  Number of iterations.
  (default 10)
```
```
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
```
```
 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.REPTree)
```
```
 
 Options specific to classifier weka.classifiers.trees.REPTree:
 
```
```
 -M <minimum number of instances>
  Set minimum number of instances per leaf (default 2).
```
```
 -V <minimum variance for split>
  Set minimum numeric class variance proportion
  of train variance for split (default 1e-3).
```
```
 -N <number of folds>
  Number of folds for reduced error pruning (default 3).
```
```
 -S <seed>
  Seed for random data shuffling (default 1).
```
```
 -P
  No pruning.
```
```
 -L
  Maximum tree depth (default -1, no maximum)
```
    Options after -- are passed to the designated classifier.
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class RandomizableIteratedSingleClassifierEnhancer
    
    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 Classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class RandomizableIteratedSingleClassifierEnhancer
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - subSpaceSizeTipText
```
public String subSpaceSizeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getSubSpaceSize
```
public double getSubSpaceSize()
```
    Gets the size of each subSpace, as a percentage of the training set size.
    
    Returns:
    
    the subSpace size, as a percentage.
  - setSubSpaceSize
```
public void setSubSpaceSize(double value)
```
    Sets the size of each subSpace, as a percentage of the training set size.
    
    Parameters:
    
    value - the subSpace size, as a percentage.
  - buildClassifier
```
public void buildClassifier(Instances data)
                     throws Exception
```
    builds the classifier.
    
    Overrides:
    
    buildClassifier in class IteratedSingleClassifierEnhancer
    
    Parameters:
    
    data - the training data to be used for generating the classifier.
    
    Throws:
    
    Exception - if the classifier could not be built successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance instance)
                                 throws Exception
```
    Calculates the class membership probabilities for the given test instance.
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    
    instance - the instance to be classified
    
    Returns:
    
    preedicted class probability distribution
    
    Throws:
    
    Exception - if distribution can't be computed successfully
  - toString
```
public String toString()
```
    Returns description of the bagged classifier.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    description of the bagged classifier as a string
  - getRevision
```
public 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(String[] args)
```
    Main method for testing this class.
    
    Parameters:
    
    args - the options

Class RandomSubSpace

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Constructor Detail

RandomSubSpace

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

subSpaceSizeTipText

getSubSpaceSize

setSubSpaceSize

buildClassifier

distributionForInstance

toString

getRevision

main