Package weka.attributeSelection
Class RankSearch
java.lang.Object
weka.attributeSelection.ASSearch
weka.attributeSelection.RankSearch
- All Implemented Interfaces:
Serializable
,OptionHandler
,RevisionHandler
,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:
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 seperate value.
- Version:
- $Revision: 6253 $
- Author:
- Mark Hall (mhall@cs.waikato.ac.nz)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionReturns the tip text for this propertyGet the attribute evaluator used to generate the ranking.String[]
Gets the current settings of WrapperSubsetEval.Returns the revision string.int
Get the point at which to start evaluating the rankingint
Get the number of attributes to add from the rankining in each iterationReturns 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 a string describing this search methodReturns an enumeration describing the available options.int[]
search
(ASEvaluation ASEval, Instances data) Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.void
setAttributeEvaluator
(ASEvaluation newEvaluator) Set the attribute evaluator to use for generating the ranking.void
setOptions
(String[] options) Parses a given list of options.void
setStartPoint
(int sp) Set the point at which to start evaluating the rankingvoid
setStepSize
(int ss) Set the number of attributes to add from the rankining in each iterationReturns the tip text for this propertyReturns the tip text for this propertytoString()
returns a description of the search as a StringMethods inherited from class weka.attributeSelection.ASSearch
forName, makeCopies
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Constructor Details
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RankSearch
public RankSearch()Constructor
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Method Details
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globalInfo
Returns a string describing this search method- Returns:
- a description of the search method suitable for displaying in the explorer/experimenter gui
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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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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attributeEvaluatorTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setAttributeEvaluator
Set the attribute evaluator to use for generating the ranking.- Parameters:
newEvaluator
- the attribute evaluator to use.
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getAttributeEvaluator
Get the attribute evaluator used to generate the ranking.- Returns:
- the evaluator used to generate the ranking.
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stepSizeTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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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.
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getStepSize
public int getStepSize()Get the number of attributes to add from the rankining in each iteration- Returns:
- the number of attributes to add.
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startPointTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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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
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getStartPoint
public int getStartPoint()Get the point at which to start evaluating the ranking- Returns:
- the position in the ranking to start at
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listOptions
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Returns:
- an enumeration of all the available options.
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setOptions
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 interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
Gets the current settings of WrapperSubsetEval.- Specified by:
getOptions
in interfaceOptionHandler
- Returns:
- an array of strings suitable for passing to setOptions()
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search
Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator. -
toString
returns a description of the search as a String -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classASSearch
- Returns:
- the revision
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