java.lang.Object
- weka.attributeSelection.ASSearch
- - weka.attributeSelection.SubsetSizeForwardSelection

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

public class SubsetSizeForwardSelection
extends ASSearch
implements OptionHandler

SubsetSizeForwardSelection:

Extension of LinearForwardSelection. The search performs an interior cross-validation (seed and number of folds can be specified). A LinearForwardSelection is performed on each foldto determine the optimal subset-size (using the given SubsetSizeEvaluator). Finally, a LinearForwardSelection up to the optimal subset-size is performed on the whole data.

For more information see:

Martin Guetlein (2006). Large Scale Attribute Selection Using Wrappers. Freiburg, Germany.

Valid options are:

 -I
  Perform initial ranking to select the
  top-ranked attributes.

 -K <num>
  Number of top-ranked attributes that are 
  taken into account by the search.

 -T <0 = fixed-set | 1 = fixed-width>
  Type of Linear Forward Selection (default = 0).

 -S <num>
  Size of lookup cache for evaluated subsets.
  Expressed as a multiple of the number of
  attributes in the data set. (default = 1)

 -E <subset evaluator>
  Subset-evaluator used for subset-size determination.-- -M

 -F <num>
  Number of cross validation folds
  for subset size determination (default = 5).

 -R <num>
  Seed for cross validation
  subset size determination. (default = 1)

 -Z
  verbose on/off

 Options specific to evaluator weka.attributeSelection.ClassifierSubsetEval:

 -B <classifier>
  class name of the classifier to use for accuracy estimation.
  Place any classifier options LAST on the command line
  following a "--". eg.:
   -B weka.classifiers.bayes.NaiveBayes ... -- -K
  (default: weka.classifiers.rules.ZeroR)

 -T
  Use the training data to estimate accuracy.

 -H <filename>
  Name of the hold out/test set to 
  estimate accuracy on.

 Options specific to scheme weka.classifiers.rules.ZeroR:

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

Version:: $Revision: 11198 $
Author:: Martin Guetlein (martin.guetlein@gmail.com)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type Field Description

static Tag[] TAGS_TYPE

Constructor Summary

Constructors
Constructor Description

SubsetSizeForwardSelection()
Constructor

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`int`	`getLookupCacheSize()`	Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
`int`	`getNumSubsetSizeCVFolds()`	Get the number of cross validation folds for subset size determination (default = 5).
`int`	`getNumUsedAttributes()`	Get the number of top-ranked attributes that taken into account by the search process.
`java.lang.String[]`	`getOptions()`	Gets the current settings of LinearForwardSelection.
`boolean`	`getPerformRanking()`	Get boolean if initial ranking should be performed to select the top-ranked attributes
`java.lang.String`	`getRevision()`	Returns the revision string.
`int`	`getSeed()`	Seed for cross validation subset size determination.
`ASEvaluation`	`getSubsetSizeEvaluator()`	Get the subset evaluator used for subset size determination.
`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.
`SelectedTag`	`getType()`	Get the type
`boolean`	`getVerbose()`	Get whether output is to be verbose
`java.lang.String`	`globalInfo()`	Returns a string describing this search method
`java.util.Enumeration`	`listOptions()`	Returns an enumeration describing the available options.
`java.lang.String`	`lookupCacheSizeTipText()`	Returns the tip text for this property
`java.lang.String`	`numSubsetSizeCVFoldsTipText()`	Returns the tip text for this property
`java.lang.String`	`numUsedAttributesTipText()`	Returns the tip text for this property
`java.lang.String`	`performRankingTipText()`	Returns the tip text for this property
`int[]`	`search(ASEvaluation ASEval, Instances data)`	Searches the attribute subset space by subset size forward selection
`java.lang.String`	`seedTipText()`	Returns the tip text for this property
`void`	`setLookupCacheSize(int size)`	Set the maximum size of the evaluated subset cache (hashtable).
`void`	`setNumSubsetSizeCVFolds(int f)`	Set the number of cross validation folds for subset size determination (default = 5).
`void`	`setNumUsedAttributes(int k)`	Set the number of top-ranked attributes that taken into account by the search process.
`void`	`setOptions(java.lang.String[] options)`	Parses a given list of options.
`void`	`setPerformRanking(boolean b)`	Perform initial ranking to select top-ranked attributes.
`void`	`setSeed(int s)`	Seed for cross validation subset size determination.
`void`	`setSubsetSizeEvaluator(ASEvaluation eval)`	Set the subset evaluator to use for subset size determination.
`void`	`setType(SelectedTag t)`	Set the type
`void`	`setVerbose(boolean b)`	Set whether verbose output should be generated.
`java.lang.String`	`subsetSizeEvaluatorTipText()`	Returns the tip text for this property
`java.lang.String`	`toString()`	returns a description of the search as a String
`java.lang.String`	`typeTipText()`	Returns the tip text for this property
`java.lang.String`	`verboseTipText()`	Returns the tip text for this property

Methods inherited from class weka.attributeSelection.ASSearch
forName, makeCopies

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

- Field Detail
  - TAGS_TYPE
```
public static final Tag[] TAGS_TYPE
```
- Constructor Detail
  - SubsetSizeForwardSelection
```
public SubsetSizeForwardSelection()
```
    Constructor
- Method Detail
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing this search method
    
    Returns:
    
    a description of the search method 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.
    
    Returns:
    
    the technical information about this class
  - listOptions
```
public java.util.Enumeration 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:
    -I
    Perform initial ranking to select top-ranked attributes.
    -K
    Number of top-ranked attributes that are taken into account.
    -T <0 = fixed-set | 1 = fixed-width>
    Typ of Linear Forward Selection (default = 0).
    -S
    Size of lookup cache for evaluated subsets. Expressed as a multiple of the number of attributes in the data set. (default = 1).
    -E
    class name of subset evaluator to use for subset size determination (default = null, same subset evaluator as for ranking and final forward selection is used). Place any evaluator options LAST on the command line following a "--". eg. -A weka.attributeSelection.ClassifierSubsetEval ... -- -M -F
    Number of cross validation folds for subset size determination (default = 5).
    -R
    Seed for cross validation subset size determination. (default = 1)
    -Z
    verbose on/off.
    
    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
  - setLookupCacheSize
```
public void setLookupCacheSize(int size)
```
    Set the maximum size of the evaluated subset cache (hashtable). This is expressed as a multiplier for the number of attributes in the data set. (default = 1).
    
    Parameters:
    
    size - the maximum size of the hashtable
  - getLookupCacheSize
```
public int getLookupCacheSize()
```
    Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
    
    Returns:
    
    the maximum size of the hashtable.
  - lookupCacheSizeTipText
```
public java.lang.String lookupCacheSizeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - performRankingTipText
```
public java.lang.String performRankingTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setPerformRanking
```
public void setPerformRanking(boolean b)
```
    Perform initial ranking to select top-ranked attributes.
    
    Parameters:
    
    b - true if initial ranking should be performed
  - getPerformRanking
```
public boolean getPerformRanking()
```
    Get boolean if initial ranking should be performed to select the top-ranked attributes
    
    Returns:
    
    true if initial ranking should be performed
  - numUsedAttributesTipText
```
public java.lang.String numUsedAttributesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNumUsedAttributes
```
public void setNumUsedAttributes(int k)
                          throws java.lang.Exception
```
    Set the number of top-ranked attributes that taken into account by the search process.
    
    Parameters:
    
    k - the number of attributes
    
    Throws:
    
    java.lang.Exception - if k is less than 2
  - getNumUsedAttributes
```
public int getNumUsedAttributes()
```
    Get the number of top-ranked attributes that taken into account by the search process.
    
    Returns:
    
    the number of top-ranked attributes that taken into account
  - typeTipText
```
public java.lang.String typeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setType
```
public void setType(SelectedTag t)
```
    Set the type
    
    Parameters:
    
    t - the Linear Forward Selection type
  - getType
```
public SelectedTag getType()
```
    Get the type
    
    Returns:
    
    the Linear Forward Selection type
  - subsetSizeEvaluatorTipText
```
public java.lang.String subsetSizeEvaluatorTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setSubsetSizeEvaluator
```
public void setSubsetSizeEvaluator(ASEvaluation eval)
                            throws java.lang.Exception
```
    Set the subset evaluator to use for subset size determination.
    
    Parameters:
    
    eval - the subset evaluator to use for subset size determination.
    
    Throws:
    
    java.lang.Exception
  - getSubsetSizeEvaluator
```
public ASEvaluation getSubsetSizeEvaluator()
```
    Get the subset evaluator used for subset size determination.
    
    Returns:
    
    the evaluator used for subset size determination.
  - numSubsetSizeCVFoldsTipText
```
public java.lang.String numSubsetSizeCVFoldsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNumSubsetSizeCVFolds
```
public void setNumSubsetSizeCVFolds(int f)
```
    Set the number of cross validation folds for subset size determination (default = 5).
    
    Parameters:
    
    f - number of folds
  - getNumSubsetSizeCVFolds
```
public int getNumSubsetSizeCVFolds()
```
    Get the number of cross validation folds for subset size determination (default = 5).
    
    Returns:
    
    number of folds
  - seedTipText
```
public java.lang.String seedTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setSeed
```
public void setSeed(int s)
```
    Seed for cross validation subset size determination. (default = 1)
    
    Parameters:
    
    s - seed
  - getSeed
```
public int getSeed()
```
    Seed for cross validation subset size determination. (default = 1)
    
    Returns:
    
    seed
  - verboseTipText
```
public java.lang.String verboseTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setVerbose
```
public void setVerbose(boolean b)
```
    Set whether verbose output should be generated.
    
    Parameters:
    
    d - true if output is to be verbose.
  - getVerbose
```
public boolean getVerbose()
```
    Get whether output is to be verbose
    
    Returns:
    
    true if output will be verbose
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings of LinearForwardSelection.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    
    an array of strings suitable for passing to setOptions()
  - toString
```
public java.lang.String toString()
```
    returns a description of the search as a String
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a description of the search
  - search
```
public int[] search(ASEvaluation ASEval,
                    Instances data)
             throws java.lang.Exception
```
    Searches the attribute subset space by subset size forward selection
    
    Specified by:
    
    search in class ASSearch
    
    Parameters:
    
    ASEvaluator - the attribute evaluator to guide the search
    
    data - the training instances.
    
    Returns:
    
    an array (not necessarily ordered) of selected attribute indexes
    
    Throws:
    
    java.lang.Exception - if the search can't be completed
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class ASSearch
    
    Returns:
    
    the revision

Class SubsetSizeForwardSelection

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASSearch

Methods inherited from class java.lang.Object

Field Detail

TAGS_TYPE

Constructor Detail

SubsetSizeForwardSelection

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

setLookupCacheSize

getLookupCacheSize

lookupCacheSizeTipText

performRankingTipText

setPerformRanking

getPerformRanking

numUsedAttributesTipText

setNumUsedAttributes

getNumUsedAttributes

typeTipText

setType

getType

subsetSizeEvaluatorTipText

setSubsetSizeEvaluator

getSubsetSizeEvaluator

numSubsetSizeCVFoldsTipText

setNumSubsetSizeCVFolds

getNumSubsetSizeCVFolds

seedTipText

setSeed

getSeed

verboseTipText

setVerbose

getVerbose

getOptions

toString

search

getRevision