ScatterSearchV1 (weka-stable 3.6.14 API)

java.lang.Object
- weka.attributeSelection.ASSearch
- - weka.attributeSelection.ScatterSearchV1

All Implemented Interfaces:: Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class ScatterSearchV1
extends ASSearch
implements OptionHandler, TechnicalInformationHandler

Class for performing the Sequential Scatter Search.

Scatter Search :

Performs an Scatter Search through the space of attribute subsets. Start with a population of many significants and diverses subset stops when the result is higher than a given treshold or there's not more improvement
For more information see:

Felix Garcia Lopez (2004). Solving feature subset selection problem by a Parallel Scatter Search. Elsevier.

Valid options are:

 -Z <num>
  Specify the number of subsets to generate 
  in the initial population..

 -T <threshold>
  Specify the treshold used for considering when a subset is significant.

 -R <0 = greedy combination | 1 = reduced greedy combination >
  Specify the kind of combiantion 
  for using it in the combination method.

 -S <seed>
  Set the random number seed.
  (default = 1)

 -D
  Verbose output for monitoring the search.

BibTeX:

 @book{Lopez2004,
    author = {Felix Garcia Lopez},
    month = {October},
    publisher = {Elsevier},
    title = {Solving feature subset selection problem by a Parallel Scatter Search},
    year = {2004},
    language = {English}
 }

from the Book: Solving feature subset selection problem by a Parallel Scatter Search, Felix Garcia Lopez.

Version:: $Revision: 6277 $
Author:: Adrian Pino ([email protected])
See Also:: Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

class ScatterSearchV1.Subset

Nested Classes
Modifier and Type	Class and Description
`class`	`ScatterSearchV1.Subset`

Field Summary

Fields
Modifier and Type Field and Description

static Tag[] TAGS_SELECTION

Fields
Modifier and Type	Field and Description
`static Tag[]`	`TAGS_SELECTION`

Constructor Summary

Constructors
Constructor and Description

ScatterSearchV1()

Constructors
Constructor and Description
`ScatterSearchV1()`

Method Summary

Methods
Modifier and Type	Method and Description
`int[]`	`attributeList(BitSet group)` converts a BitSet into a list of attribute indexes
`List<ScatterSearchV1.Subset>`	`bubbleSubsetSort(List<ScatterSearchV1.Subset> subsetList)` Sort a List of subsets according to their merits
`double`	`calculateTreshhold()` Calculate the treshold of a dataSet given an evaluator
`String`	`combinationTipText()` Returns the tip text for this property
`void`	`CombineParents()` Combine all the posible pair solutions existing in the Population
`void`	`CreatePopulation(int popSize)` Create the initial Population
`String`	`debugTipText()` Returns the tip text for this property
`List<ScatterSearchV1.Subset>`	`filterSubset(List<ScatterSearchV1.Subset> subsetList, int preferredSize)` Filter a given Lis of Subsets removing the equals subsets
`int`	`generateRandomNumber(int limit)`
`void`	`GenerateReferenceSet(List<ScatterSearchV1.Subset> ReferenceSet, int bestSolutions, int divSolutions)` Generate the a ReferenceSet containing the n best solutions and the m most diverse solutions of the initial Population.
`BitSet`	`getAllBits(List<ScatterSearchV1.Subset> subsets)` Save in Bitset all the gens that are in many others subsets.
`ScatterSearchV1.Subset`	`getBestgen(ScatterSearchV1.Subset subset, BitSet gens)` Evaluate each gen of a BitSet inserted in a Subset and get the most significant for that Subset
`SelectedTag`	`getCombination()` Get the combination
`boolean`	`getDebug()` Get whether output is to be verbose
`int`	`getIndexofBiggest(List<Integer> simDif)` get the index in a List where this have the biggest number
`String[]`	`getOptions()` Gets the current settings of ScatterSearchV1.
`int`	`getPopulationSize()` Get the population size
`String`	`getRevision()` Returns the revision string.
`int`	`getSeed()` get the value of the random number generator's seed
`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.
`double`	`getThreshold()` Get the treshold
`String`	`globalInfo()` Returns a string describing this search method
`void`	`ImproveSolutions()` Improve the solutions previously combined by adding the attributes that improve that solution
`void`	`InitPopulation(int popSize)` Creating space for introducing the population
`ScatterSearchV1.Subset`	`intersectSubsets(ScatterSearchV1.Subset subset1, ScatterSearchV1.Subset subset2)` Intersects two subsets
`ScatterSearchV1.Subset`	`joinSubsets(ScatterSearchV1.Subset subset1, ScatterSearchV1.Subset subset2)` Join two subsets
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`String`	`populationSizeTipText()` Returns the tip text for this property
`String`	`printSubset(ScatterSearchV1.Subset subset)`
`List<ScatterSearchV1.Subset>`	`RankEachAttribute()` Rank all the attributes individually acording to their merits
`int[]`	`search(ASEvaluation ASEval, Instances data)` Searches the attribute subset space using Scatter Search.
`String`	`seedTipText()` Returns the tip text for this property
`void`	`setCombination(SelectedTag c)` Set the kind of combination
`void`	`setDebug(boolean d)` Set whether verbose output should be generated.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setPopulationSize(int size)` Set the population size
`void`	`setSeed(int s)` set the seed for random number generation
`void`	`setThreshold(double threshold)` Set the treshold
`ScatterSearchV1.Subset`	`simetricDif(ScatterSearchV1.Subset subset1, ScatterSearchV1.Subset subset2, int mode)`
`int`	`SimetricDiference(ScatterSearchV1.Subset subset, BitSet bitset)` Calculate the Simetric Diference of two subsets
`String`	`thresholdTipText()` Returns the tip text for this property
`String`	`toString()` returns a description of the search.
`void`	`UpdateReferenceSet(int numBestSolutions, int numDivsSolutions)` Update the ReferenceSet putting the new obtained Solutions there

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
  - TAGS_SELECTION
```
public static final Tag[] TAGS_SELECTION
```
- Constructor Detail
  - ScatterSearchV1
```
public ScatterSearchV1()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this search method
    
    Returns:
    a description of the search suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public 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.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    the technical information about this class
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class ASSearch
    
    Returns:
    the revision
  - thresholdTipText
```
public String thresholdTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setThreshold
```
public void setThreshold(double threshold)
```
    Set the treshold
    
    Parameters:
    threshold - for identifyng significant subsets
  - getThreshold
```
public double getThreshold()
```
    Get the treshold
    
    Returns:
    the treshold that subsets most overcome to be considered as significants
  - populationSizeTipText
```
public String populationSizeTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setPopulationSize
```
public void setPopulationSize(int size)
```
    Set the population size
    
    Parameters:
    size - the number of subset in the initial population
  - getPopulationSize
```
public int getPopulationSize()
```
    Get the population size
    
    Returns:
    the number of subsets to generate in the initial population
  - combinationTipText
```
public String combinationTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setCombination
```
public void setCombination(SelectedTag c)
```
    Set the kind of combination
    
    Parameters:
    c - the kind of combination of the search
  - getCombination
```
public SelectedTag getCombination()
```
    Get the combination
    
    Returns:
    the kind of combination used in the Combination method
  - seedTipText
```
public String seedTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setSeed
```
public void setSeed(int s)
```
    set the seed for random number generation
    
    Parameters:
    s - seed value
  - getSeed
```
public int getSeed()
```
    get the value of the random number generator's seed
    
    Returns:
    the seed for random number generation
  - debugTipText
```
public String debugTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDebug
```
public void setDebug(boolean d)
```
    Set whether verbose output should be generated.
    
    Parameters:
    d - true if output is to be verbose.
  - getDebug
```
public boolean getDebug()
```
    Get whether output is to be verbose
    
    Returns:
    true if output will be verbose
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options. Valid options are:
    -Z
    Specify the number of subsets to generate in the initial population.
    -T
    Specify the treshold used for considering when a subset is significant.
    -R
    Specify the kind of combiantion.
    -S
    Set the random number seed. (default = 1) -D
    Verbose output for monitoring the search (default = false)
    
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of ScatterSearchV1.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    an array of strings suitable for passing to setOptions()
  - toString
```
public String toString()
```
    returns a description of the search.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a description of the search as a String.
  - search
```
public int[] search(ASEvaluation ASEval,
           Instances data)
             throws Exception
```
    Searches the attribute subset space using Scatter Search.
    
    Specified by:
    
    search in class ASSearch
    
    Parameters:
    ASEval - the attribute evaluator to guide the search
    data - the training instances.
    
    Returns:
    an array of selected attribute indexes
    
    Throws:
    
    Exception - if the search can't be completed
  - GenerateReferenceSet
```
public void GenerateReferenceSet(List<ScatterSearchV1.Subset> ReferenceSet,
                        int bestSolutions,
                        int divSolutions)
```
    Generate the a ReferenceSet containing the n best solutions and the m most diverse solutions of the initial Population.
    
    Parameters:
    ReferenceSet - the ReferenceSet for storing these solutions
    bestSolutions - the number of the most pure solutions.
    divSolutions - the number of the most diverses solutions acording to the bestSolutions.
  - UpdateReferenceSet
```
public void UpdateReferenceSet(int numBestSolutions,
                      int numDivsSolutions)
```
    Update the ReferenceSet putting the new obtained Solutions there
    
    Parameters:
    numBestSolutions - the number of the most pure solutions.
    numDivsSolutions - the number of the most diverses solutions acording to the bestSolutions.
  - ImproveSolutions
```
public void ImproveSolutions()
                      throws Exception
```
    Improve the solutions previously combined by adding the attributes that improve that solution
    
    Throws:
    
    Exception - if there is some trouble evaluating the candidate solutions
  - CombineParents
```
public void CombineParents()
                    throws Exception
```
    Combine all the posible pair solutions existing in the Population
    
    Throws:
    
    Exception - if there is some trouble evaluating the new childs
  - CreatePopulation
```
public void CreatePopulation(int popSize)
                      throws Exception
```
    Create the initial Population
    
    Parameters:
    popSize - the size of the initial population
    
    Throws:
    
    Exception - if there is a trouble evaluating any solution
  - RankEachAttribute
```
public List<ScatterSearchV1.Subset> RankEachAttribute()
                                               throws Exception
```
    Rank all the attributes individually acording to their merits
    
    Returns:
    an ordered List of Subsets with just one attribute
    
    Throws:
    
    Exception - if the evaluation can not be completed
  - getBestgen
```
public ScatterSearchV1.Subset getBestgen(ScatterSearchV1.Subset subset,
                                BitSet gens)
                                  throws Exception
```
    Evaluate each gen of a BitSet inserted in a Subset and get the most significant for that Subset
    
    Returns:
    a new Subset with the union of subset and the best gen of gens. in case that there's not improvement with each gen return null
    
    Throws:
    
    Exception - if the evaluation of can not be completed
  - bubbleSubsetSort
```
public List<ScatterSearchV1.Subset> bubbleSubsetSort(List<ScatterSearchV1.Subset> subsetList)
```
    Sort a List of subsets according to their merits
    
    Parameters:
    subsetList - the subsetList to be ordered
    
    Returns:
    a List with ordered subsets
  - getIndexofBiggest
```
public int getIndexofBiggest(List<Integer> simDif)
```
    get the index in a List where this have the biggest number
    
    Parameters:
    simDif - the Lists of numbers for getting from them the index of the bigger
    
    Returns:
    an index that represents where the bigest number is.
  - getAllBits
```
public BitSet getAllBits(List<ScatterSearchV1.Subset> subsets)
```
    Save in Bitset all the gens that are in many others subsets.
    
    Parameters:
    subsets - the Lists of subsets for getting from them all their gens
    
    Returns:
    a Bitset with all the gens contained in many others subsets.
  - InitPopulation
```
public void InitPopulation(int popSize)
```
    Creating space for introducing the population
    
    Parameters:
    popSize - the number of subset in the initial population
  - joinSubsets
```
public ScatterSearchV1.Subset joinSubsets(ScatterSearchV1.Subset subset1,
                                 ScatterSearchV1.Subset subset2)
                                   throws Exception
```
    Join two subsets
    
    Parameters:
    subset1 - one of the subsets
    subset2 - the other subset
    
    Returns:
    a new Subset that is te result of the Join
    
    Throws:
    
    Exception - if the evaluation of the subsets can not be completed
  - intersectSubsets
```
public ScatterSearchV1.Subset intersectSubsets(ScatterSearchV1.Subset subset1,
                                      ScatterSearchV1.Subset subset2)
                                        throws Exception
```
    Intersects two subsets
    
    Parameters:
    subset1 - one of the subsets
    subset2 - the other subset
    
    Returns:
    a new Subset that is te result of the intersection
    
    Throws:
    
    Exception - if the evaluation of the subsets can not be completed
  - simetricDif
```
public ScatterSearchV1.Subset simetricDif(ScatterSearchV1.Subset subset1,
                                 ScatterSearchV1.Subset subset2,
                                 int mode)
                                   throws Exception
```
    Throws:
    
    Exception
  - generateRandomNumber
```
public int generateRandomNumber(int limit)
```
  - calculateTreshhold
```
public double calculateTreshhold()
                          throws Exception
```
    Calculate the treshold of a dataSet given an evaluator
    
    Returns:
    the treshhold of the dataSet
    
    Throws:
    
    Exception - if the calculation can not be completed
  - SimetricDiference
```
public int SimetricDiference(ScatterSearchV1.Subset subset,
                    BitSet bitset)
```
    Calculate the Simetric Diference of two subsets
    
    Returns:
    the Simetric Diference
    
    Throws:
    
    Exception - if the calculation can not be completed
  - filterSubset
```
public List<ScatterSearchV1.Subset> filterSubset(List<ScatterSearchV1.Subset> subsetList,
                                        int preferredSize)
```
    Filter a given Lis of Subsets removing the equals subsets
    
    Parameters:
    subsetList - to filter
    preferredSize - the preferred size of the new List (if it is -1, then the filter is make it for all subsets, else then the filter method stops when the given preferred size is reached or all the subset have been filtered).
    
    Returns:
    a new List filtered
    
    Throws:
    
    Exception - if the calculation can not be completed
  - printSubset
```
public String printSubset(ScatterSearchV1.Subset subset)
```
  - attributeList
```
public int[] attributeList(BitSet group)
```
    converts a BitSet into a list of attribute indexes
    
    Parameters:
    group - the BitSet to convert
    
    Returns:
    an array of attribute indexes

Class ScatterSearchV1

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.attributeSelection.ASSearch

Methods inherited from class java.lang.Object

Field Detail

TAGS_SELECTION

Constructor Detail

ScatterSearchV1

Method Detail

globalInfo

getTechnicalInformation

getRevision

thresholdTipText

setThreshold

getThreshold

populationSizeTipText

setPopulationSize

getPopulationSize

combinationTipText

setCombination

getCombination

seedTipText

setSeed

getSeed

debugTipText

setDebug

getDebug

listOptions

setOptions

getOptions

toString

search

GenerateReferenceSet

UpdateReferenceSet

ImproveSolutions

CombineParents

CreatePopulation

RankEachAttribute

getBestgen

bubbleSubsetSort

getIndexofBiggest

getAllBits

InitPopulation

joinSubsets

intersectSubsets

simetricDif

generateRandomNumber

calculateTreshhold

SimetricDiference

filterSubset

printSubset

attributeList