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Class weka.attributeSelection.RandomSearch

java.lang.Object
   |
   +----weka.attributeSelection.ASSearch
           |
           +----weka.attributeSelection.RandomSearch

public class RandomSearch

extends ASSearch

implements StartSetHandler, OptionHandler

Valid options are:

-P
Specify a starting set of attributes. Eg 1,4,7-9.

-F Percentage of the search space to consider. (default = 25).

-V
Verbose output. Output new best subsets as the search progresses.

Version:

$Revision: 1.5 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

RandomSearch()

Constructor

getOptions()

Gets the current settings of RandomSearch.

getSearchPercent()

get the percentage of the search space to consider

getStartSet()

Returns a list of attributes (and or attribute ranges) as a String

getVerbose()

get whether or not output is verbose

listOptions()

Returns an enumeration describing the available options

search(ASEvaluation, Instances)

Searches the attribute subset space using a genetic algorithm.

setOptions(String[])

Parses a given list of options.

setSearchPercent(double)

set the percentage of the search space to consider

setStartSet(String)

Sets a starting set of attributes for the search.

setVerbose(boolean)

set whether or not to output new best subsets as the search proceeds

toString()

prints a description of the search

 public RandomSearch()

Constructor

 public Enumeration listOptions()

Returns an enumeration describing the available options

Returns:

an enumeration of all the available options

 public void setOptions(String options[]) throws Exception

Parses a given list of options. Valid options are:

-P
Specify a starting set of attributes. Eg 1,4,7-9.

-F Percentage of the search space to consider. (default = 25).

-V
Verbose output. Output new best subsets as the search progresses.

Parameters:

options - the list of options as an array of strings

Throws: Exception

if an option is not supported

 public void setStartSet(String startSet) throws Exception

Sets a starting set of attributes for the search. It is the search method's responsibility to report this start set (if any) in its toString() method.

Parameters:

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.

Throws: Exception

if start set can't be set.

 public String getStartSet()

Returns a list of attributes (and or attribute ranges) as a String

Returns:

a list of attributes (and or attribute ranges)

 public void setVerbose(boolean v)

set whether or not to output new best subsets as the search proceeds

Parameters:

v - true if output is to be verbose

 public boolean getVerbose()

get whether or not output is verbose

Returns:

true if output is set to verbose

 public void setSearchPercent(double p)

set the percentage of the search space to consider

Parameters:

p - percent of the search space ( 0 < p <= 100)

 public double getSearchPercent()

get the percentage of the search space to consider

Returns:

the percent of the search space explored

 public String[] getOptions()

Gets the current settings of RandomSearch.

Returns:

an array of strings suitable for passing to setOptions()

 public String toString()

prints a description of the search

Returns:

a description of the search as a string

Overrides:

toString in class Object

 public int[] search(ASEvaluation ASEval,
                     Instances data) throws Exception

Searches the attribute subset space using a genetic algorithm.

Parameters:

ASEvaluator - the attribute evaluator to guide the search

data - the training instances.

Returns:

an array (not necessarily ordered) of selected attribute indexes

Throws: Exception

if the search can't be completed

Overrides:

search in class ASSearch

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