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java.lang.Objectweka.attributeSelection.ASSearch
weka.attributeSelection.LinearForwardSelection
public class LinearForwardSelection
LinearForwardSelection:
Extension of BestFirst. Takes a restricted number of k attributes into account. Fixed-set selects a fixed number k of attributes, whereas k is increased in each step when fixed-width is selected. The search uses either the initial ordering to select the top k attributes, or performs a ranking (with the same evalutator the search uses later on). The search direction can be forward, or floating forward selection (with opitional backward search steps).
For more information see:
Martin Guetlein (2006). Large Scale Attribute Selection Using Wrappers. Freiburg, Germany.
-P <start set> Specify a starting set of attributes. Eg. 1,3,5-7.
-D <0 = forward selection | 1 = floating forward selection> Forward selection method. (default = 0).
-N <num> Number of non-improving nodes to consider before terminating search.
-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)
-Z verbose on/off
| Field Summary | |
|---|---|
static Tag[] |
TAGS_SEARCH_METHOD
|
static Tag[] |
TAGS_TYPE
|
| Constructor Summary | |
|---|---|
LinearForwardSelection()
Constructor |
|
| Method Summary | |
|---|---|
java.lang.String |
forwardSelectionMethodTipText()
Returns the tip text for this property |
SelectedTag |
getForwardSelectionMethod()
Get the search direction |
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 |
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 |
getSearchTermination()
Get the termination criterion (number of non-improving nodes). |
java.lang.String |
getStartSet()
Returns a list of attributes (and or attribute ranges) as a String |
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 |
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 linear forward selection |
java.lang.String |
searchTerminationTipText()
Returns the tip text for this property |
void |
setForwardSelectionMethod(SelectedTag d)
Set the search direction |
void |
setLookupCacheSize(int size)
Set the maximum size of the evaluated subset cache (hashtable). |
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 |
setSearchTermination(int t)
Set the numnber of non-improving nodes to consider before terminating search. |
void |
setStartSet(java.lang.String startSet)
Sets a starting set of attributes for the search. |
void |
setType(SelectedTag t)
Set the type |
void |
setVerbose(boolean b)
Set whether verbose output should be generated. |
java.lang.String |
startSetTipText()
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 |
| Methods inherited from class weka.attributeSelection.ASSearch |
|---|
forName, makeCopies |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Field Detail |
|---|
public static final Tag[] TAGS_SEARCH_METHOD
public static final Tag[] TAGS_TYPE
| Constructor Detail |
|---|
public LinearForwardSelection()
| Method Detail |
|---|
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic java.util.Enumeration listOptions()
listOptions in interface OptionHandler
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-P
-D <0 = forward selection | 1 = floating forward selection>
-N
-I
-K
-T <0 = fixed-set | 1 = fixed-width>
-S
-Z
Specify a starting set of attributes. Eg 1,4,7-9.
Forward selection method of the search. (default = 0).
Number of non improving nodes to consider before terminating search.
(default = 5).
Perform initial ranking to select top-ranked attributes.
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).
verbose on/off.
setOptions in interface OptionHandler
options - the list of options as an array of strings
java.lang.Exception - if an option is not supported
public void setLookupCacheSize(int size)
size - the maximum size of the hashtablepublic int getLookupCacheSize()
public java.lang.String lookupCacheSizeTipText()
public java.lang.String startSetTipText()
public void setStartSet(java.lang.String startSet)
throws java.lang.Exception
setStartSet in interface StartSetHandlerstartSet - a string containing a list of attributes (and or ranges), eg.
1,2,6,10-15.
java.lang.Exception - if start set can't be set.public java.lang.String getStartSet()
getStartSet in interface StartSetHandlerpublic java.lang.String searchTerminationTipText()
public void setSearchTermination(int t)
throws java.lang.Exception
t - the number of non-improving nodes
java.lang.Exception - if t is less than 1public int getSearchTermination()
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 attributes
java.lang.Exception - if k is less than 2public int getNumUsedAttributes()
public java.lang.String forwardSelectionMethodTipText()
public void setForwardSelectionMethod(SelectedTag d)
d - the direction of the searchpublic SelectedTag getForwardSelectionMethod()
public java.lang.String typeTipText()
public void setType(SelectedTag t)
t - the Linear Forward Selection typepublic SelectedTag getType()
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 OptionHandlerpublic java.lang.String toString()
toString in class java.lang.Object
public int[] search(ASEvaluation ASEval,
Instances data)
throws java.lang.Exception
search in class ASSearchASEvaluator - the attribute evaluator to guide the searchdata - the training instances.
java.lang.Exception - if the search can't be completedpublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class ASSearch
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