RankSearch

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

All Implemented Interfaces:

java.io.Serializable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler
```
public class RankSearch
extends weka.attributeSelection.ASSearch
implements weka.core.OptionHandler, weka.core.TechnicalInformationHandler
```
RankSearch :

Uses an attribute/subset evaluator to rank all attributes. If a subset evaluator is specified, then a forward selection search is used to generate a ranked list. From the ranked list of attributes, subsets of increasing size are evaluated, ie. The best attribute, the best attribute plus the next best attribute, etc.... The best attribute set is reported. RankSearch is linear in the number of attributes if a simple attribute evaluator is used such as GainRatioAttributeEval. For more information see:

Mark Hall, Geoffrey Holmes (2003). Benchmarking attribute selection techniques for discrete class data mining. IEEE Transactions on Knowledge and Data Engineering. 15(6):1437-1447.
Valid options are:
```
 -A <attribute evaluator>
  class name of attribute evaluator to use for ranking. Place any
  evaluator options LAST on the command line following a "--".
  eg.:
   -A weka.attributeSelection.GainRatioAttributeEval ... -- -M
  (default: weka.attributeSelection.GainRatioAttributeEval)
 
```
```
 -S <step size>
  number of attributes to be added from the
  ranking in each iteration (default = 1).
 
```
```
 -R <start point>
  point in the ranking to start evaluating from. 
  (default = 0, ie. the head of the ranking).
 
```
```
 Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
 
```
```
 -M
  treat missing values as a separate value.
 
```
Version:

$Revision: 10325 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor and Description

RankSearch()
Constructor

Constructors
Constructor and Description
`RankSearch()` Constructor

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`attributeEvaluatorTipText()` Returns the tip text for this property
`java.lang.String`	`debuggingOutputTipText()` Returns the tip text for this property
`java.lang.String`	`excludeNonImprovingAttributesTipText()` Returns the tip text for this property
`weka.attributeSelection.ASEvaluation`	`getAttributeEvaluator()` Get the attribute evaluator used to generate the ranking.
`boolean`	`getDebuggingOutput()` Get whether to output debugging info to the console
`boolean`	`getExcludeNonImprovingAttributes()` Get whether or not to add prior non-improving attributes when considering more attributes from the ranked list
`double`	`getImprovementThreshold()` Get merit improvement threshold
`int`	`getNonImprovingAdditions()` Get the number of consecutive non-improving additions to tolerate before terminating the search
`java.lang.String[]`	`getOptions()` Gets the current settings of WrapperSubsetEval.
`java.lang.String`	`getRevision()` Returns the revision string.
`int`	`getStartPoint()` Get the point at which to start evaluating the ranking
`int`	`getStepSize()` Get the number of attributes to add from the rankining in each iteration
`weka.core.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.
`java.lang.String`	`globalInfo()` Returns a string describing this search method
`java.lang.String`	`improvementThresholdTipText()` Returns the tip text for this property
`java.util.Enumeration<weka.core.Option>`	`listOptions()` Returns an enumeration describing the available options.
`java.lang.String`	`nonImprovingAdditionsTipText()` Returns the tip text for this property
`int[]`	`search(weka.attributeSelection.ASEvaluation ASEval, weka.core.Instances data)` Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
`void`	`setAttributeEvaluator(weka.attributeSelection.ASEvaluation newEvaluator)` Set the attribute evaluator to use for generating the ranking.
`void`	`setDebuggingOutput(boolean d)` Set whether to output debugging info to the console
`void`	`setExcludeNonImprovingAttributes(boolean b)` Set whether or not to add prior non-improving attributes when considering more attributes from the ranked list
`void`	`setImprovementThreshold(double t)` Set merit improvement threshold
`void`	`setNonImprovingAdditions(int t)` Set the number of consecutive non-improving additions to tolerate before terminating the search
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setStartPoint(int sp)` Set the point at which to start evaluating the ranking
`void`	`setStepSize(int ss)` Set the number of attributes to add from the rankining in each iteration
`java.lang.String`	`startPointTipText()` Returns the tip text for this property
`java.lang.String`	`stepSizeTipText()` Returns the tip text for this property
`java.lang.String`	`toString()` returns a description of the search as a String

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

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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - RankSearch
```
public RankSearch()
```
    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 weka.core.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 weka.core.TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - attributeEvaluatorTipText
```
public java.lang.String attributeEvaluatorTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setAttributeEvaluator
```
public void setAttributeEvaluator(weka.attributeSelection.ASEvaluation newEvaluator)
```
    Set the attribute evaluator to use for generating the ranking.
    
    Parameters:
    
    newEvaluator - the attribute evaluator to use.
  - getAttributeEvaluator
```
public weka.attributeSelection.ASEvaluation getAttributeEvaluator()
```
    Get the attribute evaluator used to generate the ranking.
    
    Returns:
    
    the evaluator used to generate the ranking.
  - stepSizeTipText
```
public java.lang.String stepSizeTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setStepSize
```
public void setStepSize(int ss)
```
    Set the number of attributes to add from the rankining in each iteration
    
    Parameters:
    
    ss - the number of attribes to add.
  - getStepSize
```
public int getStepSize()
```
    Get the number of attributes to add from the rankining in each iteration
    
    Returns:
    
    the number of attributes to add.
  - startPointTipText
```
public java.lang.String startPointTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setStartPoint
```
public void setStartPoint(int sp)
```
    Set the point at which to start evaluating the ranking
    
    Parameters:
    
    sp - the position in the ranking to start at
  - getStartPoint
```
public int getStartPoint()
```
    Get the point at which to start evaluating the ranking
    
    Returns:
    
    the position in the ranking to start at
  - debuggingOutputTipText
```
public java.lang.String debuggingOutputTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDebuggingOutput
```
public void setDebuggingOutput(boolean d)
```
    Set whether to output debugging info to the console
    
    Parameters:
    
    d - true if dubugging info is to be output
  - getDebuggingOutput
```
public boolean getDebuggingOutput()
```
    Get whether to output debugging info to the console
    
    Returns:
    
    true if dubugging info is to be output
  - improvementThresholdTipText
```
public java.lang.String improvementThresholdTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setImprovementThreshold
```
public void setImprovementThreshold(double t)
```
    Set merit improvement threshold
    
    Parameters:
    
    t - improvement threshold
  - getImprovementThreshold
```
public double getImprovementThreshold()
```
    Get merit improvement threshold
    
    Returns:
    
    improvement threshold
  - excludeNonImprovingAttributesTipText
```
public java.lang.String excludeNonImprovingAttributesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setExcludeNonImprovingAttributes
```
public void setExcludeNonImprovingAttributes(boolean b)
```
    Set whether or not to add prior non-improving attributes when considering more attributes from the ranked list
    
    Parameters:
    
    b - true if prior non-improving attributes should be omitted
  - getExcludeNonImprovingAttributes
```
public boolean getExcludeNonImprovingAttributes()
```
    Get whether or not to add prior non-improving attributes when considering more attributes from the ranked list
    
    Returns:
    
    true if prior non-improving attributes should be omitted
  - nonImprovingAdditionsTipText
```
public java.lang.String nonImprovingAdditionsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNonImprovingAdditions
```
public void setNonImprovingAdditions(int t)
```
    Set the number of consecutive non-improving additions to tolerate before terminating the search
    
    Parameters:
    
    t - the number of non-improving additions to allow
  - getNonImprovingAdditions
```
public int getNonImprovingAdditions()
```
    Get the number of consecutive non-improving additions to tolerate before terminating the search
    
    Returns:
    
    the number of non-improving additions to allow
  - listOptions
```
public java.util.Enumeration<weka.core.Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    listOptions in class weka.attributeSelection.ASSearch
    
    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:
```
 -A <attribute evaluator>
  class name of attribute evaluator to use for ranking. Place any
  evaluator options LAST on the command line following a "--".
  eg.:
   -A weka.attributeSelection.GainRatioAttributeEval ... -- -M
  (default: weka.attributeSelection.GainRatioAttributeEval)
 
```
```
 -S <step size>
  number of attributes to be added from the
  ranking in each iteration (default = 1).
 
```
```
 -R <start point>
  point in the ranking to start evaluating from. 
  (default = 0, ie. the head of the ranking).
 
```
```
 Options specific to evaluator weka.attributeSelection.GainRatioAttributeEval:
 
```
```
 -M
  treat missing values as a seperate value.
 
```
    Specified by:
    
    setOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    setOptions in class weka.attributeSelection.ASSearch
    
    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 WrapperSubsetEval.
    
    Specified by:
    
    getOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    getOptions in class weka.attributeSelection.ASSearch
    
    Returns:
    
    an array of strings suitable for passing to setOptions()
  - search
```
public int[] search(weka.attributeSelection.ASEvaluation ASEval,
                    weka.core.Instances data)
             throws java.lang.Exception
```
    Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
    
    Specified by:
    
    search in class weka.attributeSelection.ASSearch
    
    Parameters:
    
    ASEval - the subset 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
  - 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
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface weka.core.RevisionHandler
    
    Overrides:
    
    getRevision in class weka.attributeSelection.ASSearch
    
    Returns:
    
    the revision

Class RankSearch

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASSearch

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

RankSearch

Method Detail

globalInfo

getTechnicalInformation

attributeEvaluatorTipText

setAttributeEvaluator

getAttributeEvaluator

stepSizeTipText

setStepSize

getStepSize

startPointTipText

setStartPoint

getStartPoint

debuggingOutputTipText

setDebuggingOutput

getDebuggingOutput

improvementThresholdTipText

setImprovementThreshold

getImprovementThreshold

excludeNonImprovingAttributesTipText

setExcludeNonImprovingAttributes

getExcludeNonImprovingAttributes

nonImprovingAdditionsTipText

setNonImprovingAdditions

getNonImprovingAdditions

listOptions

setOptions

getOptions

search

toString

getRevision