Class SubsetSizeForwardSelection
- All Implemented Interfaces:
Serializable
,OptionHandler
,RevisionHandler
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:
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Field Summary
Fields -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionint
Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.int
Get the number of cross validation folds for subset size determination (default = 5).int
Get the number of top-ranked attributes that taken into account by the search process.String[]
Gets the current settings of LinearForwardSelection.boolean
Get boolean if initial ranking should be performed to select the top-ranked attributesReturns the revision string.int
getSeed()
Seed for cross validation subset size determination.Get the subset evaluator used for subset size determination.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.getType()
Get the typeboolean
Get whether output is to be verboseReturns a string describing this search methodReturns an enumeration describing the available options.Returns the tip text for this propertyReturns the tip text for this propertyReturns the tip text for this propertyReturns the tip text for this propertyint[]
search
(ASEvaluation ASEval, Instances data) Searches the attribute subset space by subset size forward selectionReturns the tip text for this propertyvoid
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
(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
Set the subset evaluator to use for subset size determination.void
Set the typevoid
setVerbose
(boolean b) Set whether verbose output should be generated.Returns the tip text for this propertytoString()
returns a description of the search as a StringReturns the tip text for this propertyReturns the tip text for this propertyMethods inherited from class weka.attributeSelection.ASSearch
forName, makeCopies
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Field Details
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TAGS_TYPE
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Constructor Details
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SubsetSizeForwardSelection
public SubsetSizeForwardSelection()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.- Returns:
- the technical information about this class
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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:-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 interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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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
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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.
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lookupCacheSizeTipText
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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performRankingTipText
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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setPerformRanking
public void setPerformRanking(boolean b) Perform initial ranking to select top-ranked attributes.- Parameters:
b
- true if initial ranking should be performed
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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
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numUsedAttributesTipText
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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setNumUsedAttributes
Set the number of top-ranked attributes that taken into account by the search process.- Parameters:
k
- the number of attributes- Throws:
Exception
- if k is less than 2
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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
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typeTipText
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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setType
Set the type- Parameters:
t
- the Linear Forward Selection type
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getType
Get the type- Returns:
- the Linear Forward Selection type
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subsetSizeEvaluatorTipText
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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setSubsetSizeEvaluator
Set the subset evaluator to use for subset size determination.- Parameters:
eval
- the subset evaluator to use for subset size determination.- Throws:
Exception
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getSubsetSizeEvaluator
Get the subset evaluator used for subset size determination.- Returns:
- the evaluator used for subset size determination.
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numSubsetSizeCVFoldsTipText
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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setNumSubsetSizeCVFolds
public void setNumSubsetSizeCVFolds(int f) Set the number of cross validation folds for subset size determination (default = 5).- Parameters:
f
- number of folds
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getNumSubsetSizeCVFolds
public int getNumSubsetSizeCVFolds()Get the number of cross validation folds for subset size determination (default = 5).- Returns:
- number of folds
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seedTipText
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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setSeed
public void setSeed(int s) Seed for cross validation subset size determination. (default = 1)- Parameters:
s
- seed
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getSeed
public int getSeed()Seed for cross validation subset size determination. (default = 1)- Returns:
- seed
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verboseTipText
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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setVerbose
public void setVerbose(boolean b) Set whether verbose output should be generated.- Parameters:
d
- true if output is to be verbose.
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getVerbose
public boolean getVerbose()Get whether output is to be verbose- Returns:
- true if output will be verbose
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getOptions
Gets the current settings of LinearForwardSelection.- Specified by:
getOptions
in interfaceOptionHandler
- Returns:
- an array of strings suitable for passing to setOptions()
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toString
returns a description of the search as a String -
search
Searches the attribute subset space by subset size forward selection -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classASSearch
- Returns:
- the revision
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