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java.lang.Objectweka.attributeSelection.ASSearch
weka.attributeSelection.RaceSearch
public class RaceSearch
Class for performing a racing search.
For more information see:
Moore, A. W. and Lee, M. S. (1994). Efficient algorithms for minimising
cross validation error. Proceedings of the Eleventh International
Conference on Machine Learning. pp 190--198.
Valid options are:
-R race type
0 = forward, 1 = backward, 2 = schemata, 3 = rank.
-L significance level
significance level to use for t-tests.
-T threshold
threshold for considering mean errors of two subsets the same
-F xval type
0 = 10 fold, 1 = leave-one-out (selected automatically for schemata race
-A attribute evaluator
the attribute evaluator to use when doing a rank search
-Q
produce a ranked list of attributes. Selecting this option forces
the race type to be forward. Racing continues until *all* attributes
have been selected, thus producing a ranked list of attributes.
-N number to retain
Specify the number of attributes to retain. Overides any threshold.
Use in conjunction with -Q.
-J threshold
Specify a threshold by which the AttributeSelection module can discard
attributes. Use in conjunction with -Q.
-Z
Turn on verbose output for monitoring the search
Field Summary | |
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static Tag[] |
TAGS_SELECTION
|
static Tag[] |
XVALTAGS_SELECTION
|
Constructor Summary | |
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RaceSearch()
|
Method Summary | |
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java.lang.String |
attributeEvaluatorTipText()
Returns the tip text for this property |
java.lang.String |
debugTipText()
Returns the tip text for this property |
java.lang.String |
foldsTipText()
Returns the tip text for this property |
java.lang.String |
generateRankingTipText()
Returns the tip text for this property |
ASEvaluation |
getAttributeEvaluator()
Get the attribute evaluator used to generate the ranking. |
int |
getCalculatedNumToSelect()
Gets the calculated number of attributes to retain. |
boolean |
getDebug()
Get whether output is to be verbose |
SelectedTag |
getFoldsType()
Get the xfold type |
boolean |
getGenerateRanking()
Gets whether ranking has been requested. |
int |
getNumToSelect()
Gets the number of attributes to be retained. |
java.lang.String[] |
getOptions()
Gets the current settings of BestFirst. |
SelectedTag |
getRaceType()
Get the race type |
double |
getSelectionThreshold()
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking. |
double |
getSignificanceLevel()
Get the significance level |
double |
getThreshold()
Get the threshold |
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 |
numToSelectTipText()
Returns the tip text for this property |
java.lang.String |
raceTypeTipText()
Returns the tip text for this property |
double[][] |
rankedAttributes()
Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst. |
int[] |
search(ASEvaluation ASEval,
Instances data)
Searches the attribute subset space by racing cross validation errors of competing subsets |
java.lang.String |
selectionThresholdTipText()
Returns the tip text for this property |
void |
setAttributeEvaluator(ASEvaluation newEvaluator)
Set the attribute evaluator to use for generating the ranking. |
void |
setDebug(boolean d)
Set whether verbose output should be generated. |
void |
setFoldsType(SelectedTag d)
Set the xfold type |
void |
setGenerateRanking(boolean doRank)
Records whether the user has requested a ranked list of attributes. |
void |
setNumToSelect(int n)
Specify the number of attributes to select from the ranked list (if generating a ranking). |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setRaceType(SelectedTag d)
Set the race type |
void |
setSelectionThreshold(double threshold)
Set the threshold by which the AttributeSelection module can discard attributes. |
void |
setSignificanceLevel(double sig)
Sets the significance level to use |
void |
setThreshold(double t)
Sets the threshold for comparisons |
java.lang.String |
significanceLevelTipText()
Returns the tip text for this property |
java.lang.String |
thresholdTipText()
Returns the tip text for this property |
java.lang.String |
toString()
|
Methods inherited from class weka.attributeSelection.ASSearch |
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forName |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
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public static final Tag[] TAGS_SELECTION
public static final Tag[] XVALTAGS_SELECTION
Constructor Detail |
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public RaceSearch()
Method Detail |
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public java.lang.String globalInfo()
public java.lang.String raceTypeTipText()
public void setRaceType(SelectedTag d)
d
- the type of racepublic SelectedTag getRaceType()
public java.lang.String significanceLevelTipText()
public void setSignificanceLevel(double sig)
sig
- the significance levelpublic double getSignificanceLevel()
public java.lang.String thresholdTipText()
public void setThreshold(double t)
setThreshold
in interface RankedOutputSearch
t
- the threshold to usepublic double getThreshold()
getThreshold
in interface RankedOutputSearch
public java.lang.String foldsTipText()
public void setFoldsType(SelectedTag d)
d
- the type of xvalpublic SelectedTag getFoldsType()
public java.lang.String debugTipText()
public void setDebug(boolean d)
d
- true if output is to be verbose.public boolean getDebug()
public java.lang.String attributeEvaluatorTipText()
public void setAttributeEvaluator(ASEvaluation newEvaluator)
newEvaluator
- the attribute evaluator to use.public ASEvaluation getAttributeEvaluator()
public java.lang.String generateRankingTipText()
public void setGenerateRanking(boolean doRank)
setGenerateRanking
in interface RankedOutputSearch
doRank
- true if ranking is requestedpublic boolean getGenerateRanking()
getGenerateRanking
in interface RankedOutputSearch
public java.lang.String numToSelectTipText()
public void setNumToSelect(int n)
setNumToSelect
in interface RankedOutputSearch
n
- the number of attributes to retainpublic int getNumToSelect()
getNumToSelect
in interface RankedOutputSearch
public int getCalculatedNumToSelect()
getCalculatedNumToSelect
in interface RankedOutputSearch
public java.lang.String selectionThresholdTipText()
public void setSelectionThreshold(double threshold)
threshold
- the threshold.public double getSelectionThreshold()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-R race type
0 = forward, 1 = backward, 2 = schemata, 3 = rank.
-L significance level
significance level to use for t-tests.
-T threshold
threshold for considering mean errors of two subsets the same
-F xval type
0 = 10 fold, 1 = leave-one-out (selected automatically for schemata race
-A attribute evaluator
the attribute evaluator to use when doing a rank search
-Q
produce a ranked list of attributes. Selecting this option forces
the race type to be forward. Racing continues until *all* attributes
have been selected, thus producing a ranked list of attributes.
-N number to retain
Specify the number of attributes to retain. Overides any threshold.
Use in conjunction with -Q.
-J threshold
Specify a threshold by which the AttributeSelection module can discard
attributes. Use in conjunction with -Q.
-Z
Turn on verbose output for monitoring the search
setOptions
in interface OptionHandler
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public int[] search(ASEvaluation ASEval, Instances data) throws java.lang.Exception
search
in class ASSearch
ASEvaluator
- the attribute evaluator to guide the searchdata
- the training instances.
java.lang.Exception
- if the search can't be completedpublic double[][] rankedAttributes() throws java.lang.Exception
RankedOutputSearch
rankedAttributes
in interface RankedOutputSearch
java.lang.Exception
- if the ranking can't be producedpublic java.lang.String toString()
toString
in class java.lang.Object
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