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java.lang.Objectweka.attributeSelection.ASSearch
weka.attributeSelection.RandomSearch
public class RandomSearch
RandomSearch :
Performs a Random search in the space of attribute subsets. If no start set is supplied, Random search starts from a random point and reports the best subset found. If a start set is supplied, Random searches randomly for subsets that are as good or better than the start point with the same or or fewer attributes. Using RandomSearch in conjunction with a start set containing all attributes equates to the LVF algorithm of Liu and Setiono (ICML-96).
For more information see:
H. Liu, R. Setiono: A probabilistic approach to feature selection - A filter solution. In: 13th International Conference on Machine Learning, 319-327, 1996.
@inproceedings{Liu1996, author = {H. Liu and R. Setiono}, booktitle = {13th International Conference on Machine Learning}, pages = {319-327}, title = {A probabilistic approach to feature selection - A filter solution}, year = {1996} }Valid options are:
-P <start set> Specify a starting set of attributes. Eg. 1,3,5-7. If a start point is supplied, random search evaluates the start point and then randomly looks for subsets that are as good as or better than the start point with the same or lower cardinality.
-F <percent> Percent of search space to consider. (default = 25%).
-V Output subsets as the search progresses. (default = false).
-seed <num> Random seed (default = 1)
Constructor Summary | |
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RandomSearch()
Constructor |
Method Summary | |
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java.lang.String[] |
getOptions()
Gets the current settings of RandomSearch. |
java.lang.String |
getRevision()
Returns the revision string. |
double |
getSearchPercent()
get the percentage of the search space to consider |
int |
getSeed()
Get the random seed to use |
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. |
boolean |
getVerbose()
get whether or not output is verbose |
java.lang.String |
globalInfo()
Returns a string describing this search method |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
int[] |
search(ASEvaluation ASEval,
Instances data)
Searches the attribute subset space randomly. |
java.lang.String |
searchPercentTipText()
Returns the tip text for this property |
java.lang.String |
seedTipText()
Returns the tip text for this property |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setSearchPercent(double p)
set the percentage of the search space to consider |
void |
setSeed(int seed)
Set the random seed to use |
void |
setStartSet(java.lang.String startSet)
Sets a starting set of attributes for the search. |
void |
setVerbose(boolean v)
set whether or not to output new best subsets as the search proceeds |
java.lang.String |
startSetTipText()
Returns the tip text for this property |
java.lang.String |
toString()
prints a description of the search |
java.lang.String |
verboseTipText()
Returns the tip text for this property |
Methods inherited from class weka.attributeSelection.ASSearch |
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forName, makeCopies |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public RandomSearch()
Method Detail |
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public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-P <start set> Specify a starting set of attributes. Eg. 1,3,5-7. If a start point is supplied, random search evaluates the start point and then randomly looks for subsets that are as good as or better than the start point with the same or lower cardinality.
-F <percent> Percent of search space to consider. (default = 25%).
-V Output subsets as the search progresses. (default = false).
-seed <num> Random seed (default = 1)
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 java.lang.String startSetTipText()
public void setStartSet(java.lang.String startSet) throws java.lang.Exception
setStartSet
in interface StartSetHandler
startSet
- a string containing a list of attributes (and or ranges),
eg. 1,2,6,10-15. "" indicates no start point.
If a start point is supplied, random search evaluates the
start point and then looks for subsets that are as good as or better
than the start point with the same or lower cardinality.
java.lang.Exception
- if start set can't be set.public java.lang.String getStartSet()
getStartSet
in interface StartSetHandler
public java.lang.String verboseTipText()
public void setVerbose(boolean v)
v
- true if output is to be verbosepublic boolean getVerbose()
public java.lang.String searchPercentTipText()
public void setSearchPercent(double p)
p
- percent of the search space ( 0 < p <= 100)public java.lang.String seedTipText()
public void setSeed(int seed)
seed
- the seed to usepublic int getSeed()
public double getSearchPercent()
public java.lang.String toString()
toString
in class java.lang.Object
public int[] search(ASEvaluation ASEval, Instances data) throws java.lang.Exception
search
in class ASSearch
ASEval
- 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 RevisionHandler
getRevision
in class ASSearch
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