public class SubsetSizeForwardSelection extends ASSearch implements OptionHandler
-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
Constructor and Description |
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SubsetSizeForwardSelection()
Constructor
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Modifier and Type | Method and Description |
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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
|
forName, makeCopies
public static final Tag[] TAGS_TYPE
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-I
Perform initial ranking to select top-ranked attributes.
-K
-T <0 = fixed-set | 1 = fixed-width>
-S
-E
-R
-Z
Number of top-ranked attributes that are taken into account.
Typ of Linear Forward Selection (default = 0).
Size of lookup cache for evaluated subsets. Expressed as a multiple of the
number of attributes in the data set. (default = 1).
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).
Seed for cross validation subset size determination. (default = 1)
verbose on/off.
setOptions
in interface OptionHandler
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic void setLookupCacheSize(int size)
size
- the maximum size of the hashtablepublic int getLookupCacheSize()
public java.lang.String lookupCacheSizeTipText()
public java.lang.String performRankingTipText()
public void setPerformRanking(boolean b)
b
- true if initial ranking should be performedpublic boolean getPerformRanking()
public java.lang.String numUsedAttributesTipText()
public void setNumUsedAttributes(int k) throws java.lang.Exception
k
- the number of attributesjava.lang.Exception
- if k is less than 2public int getNumUsedAttributes()
public java.lang.String typeTipText()
public void setType(SelectedTag t)
t
- the Linear Forward Selection typepublic SelectedTag getType()
public java.lang.String subsetSizeEvaluatorTipText()
public void setSubsetSizeEvaluator(ASEvaluation eval) throws java.lang.Exception
eval
- the subset evaluator to use for subset size determination.java.lang.Exception
public ASEvaluation getSubsetSizeEvaluator()
public java.lang.String numSubsetSizeCVFoldsTipText()
public void setNumSubsetSizeCVFolds(int f)
f
- number of foldspublic int getNumSubsetSizeCVFolds()
public java.lang.String seedTipText()
public void setSeed(int s)
s
- seedpublic int getSeed()
public java.lang.String verboseTipText()
public void setVerbose(boolean b)
d
- true if output is to be verbose.public boolean getVerbose()
public java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public java.lang.String toString()
toString
in class java.lang.Object
public int[] search(ASEvaluation ASEval, Instances data) throws java.lang.Exception
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class ASSearch