Genetic

java.lang.Object
- keel.Algorithms.Subgroup_Discovery.SDIGA.SDIGA.Genetic

```
public class Genetic
extends java.lang.Object
```
Methods to define the genetic algorithm and to apply operators and reproduction schema

Since:

JDK1.5

Version:

2.0

Author:

Writed by Pedro González (University of Jaen) 22/08/2004, Modified by Pedro González (University of Jaen) 4/08/2007, Modified by Cristóbal J. Carmona (University of Jaen) 20/04/2010

Constructor Summary

Constructors
Constructor and Description

Genetic()
Creates a new instance of Genetic

Constructors
Constructor and Description
`Genetic()` Creates a new instance of Genetic

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`evalIndiv(int pos, Genetic AG, TableVar Variables, TableDat Examples, boolean marcar)` Evaluates an individual of the main population
`void`	`GeneticAlgorithm(TableVar Variables, TableDat Examples, java.lang.String nFile)` Composes the genetic algorithm applying the operators
`int`	`getBestGuy()` Return the position of the best individual of the main population
`CromCAN`	`getIndivCromCAN(int pos)` Returns de hole chromosome of the selected individual
`CromDNF`	`getIndivCromDNF(int pos)` Returns de hole chromosome of the selected individual
`int`	`getLenghtPop()` Methods to get the lenght of the population
`boolean`	`getLSearch()` Methods to get if local search must be performed
`float`	`getMinConf()` Methods to get the value for the minimum confidence of the rules to be generated
`int`	`getNEval()` Methods to get the number of evaluation to perform in an iteration of the GA
`java.lang.String`	`getObj(int pos)` Methods to get the name of the quality measure as objective in a position
`java.lang.String`	`getObj1()` Methods to get the name of the quality measure as objective 1
`java.lang.String`	`getObj2()` Methods to get the name of the quality measure as objective 2
`java.lang.String`	`getObj3()` Methods to get the name of the quality measure as objective 3
`float`	`getProbCross()` Methods to get the value for the crossover probability
`float`	`getProbMut()` Methods to get the value for the mutation probability
`QualityMeasures`	`getQualityMeasures(int pos, java.lang.String nFile)` Get the measures of a single rule of the main population
`java.lang.String`	`getRulesRep()` Gets the representation of the rules
`float`	`getW(int pos)` Methods to get the value for the weight of the objective in a position
`float`	`getW1()` Methods to get the value for the weight of the objective 1
`float`	`getW2()` Methods to get the value for the weight of the objective 2
`float`	`getW3()` Methods to get the value for the weight of the objective 3
`boolean`	`LocalImprovementCAN(TableVar Variables, TableDat Examples)` Locally improves the rule generated.
`boolean`	`LocalImprovementDNF(TableVar Variables, TableDat Examples)` Locally improves the rule generated.
`void`	`MultipointCrossoverCAN(TableVar Variables)` Cross operator for the genetic algorithm, where only cross the two better individuals
`void`	`MultipointCrossoverDNF(TableVar Variables)` Cross operator for the genetic algorithm, where only cross the two better individuals
`void`	`MutationCAN(TableVar Variables)` Applies the mutation operator.
`void`	`MutationDNF(TableVar Variables)` Applies the mutation operator.
`void`	`SelectCAN(TableVar Variables)` Applies the selection schema of the genetic algorithm
`void`	`SelectDNF(TableVar Variables)` Applies the selection schema of the genetic algorithm
`void`	`setLenghtPop(int value)` Methods to set the lenght of the population
`void`	`setLSearch(boolean value)` Methods to set if local search must be performed
`void`	`setMinConf(float value)` Methods to set the value for the minimum confidence of the rules to be generated
`void`	`setMuNext(int value)` Sets the value for indicating the position of the next mutation
`void`	`setNEval(int value)` Methods to set the number of evaluation to perform in an iteration of the GA
`void`	`setObj1(java.lang.String value)` Methods to set the value for the quality measures as objective 1
`void`	`setObj2(java.lang.String value)` Methods to set the value for the quality measures as objective 2
`void`	`setObj3(java.lang.String value)` Methods to set the value for the quality measures as objective 3
`void`	`setProbCross(float value)` Methods to set the value for the crossover probability
`void`	`setProbMut(float value)` Methods to set the value for the mutation probability
`void`	`setRulesRep(java.lang.String value)` Sets the representation of the rules
`void`	`setW1(float value)` Methods to set the value for the weight of the objective 1
`void`	`setW2(float value)` Methods to set the value for the weight of the objective 2
`void`	`setW3(float value)` Methods to set the value for the weight of the objective 3
`void`	`SteadyStepReproductionCAN(TableVar Variables)` Uses a Steady Step method
`void`	`SteadyStepReproductionDNF(TableVar Variables)` Uses a Steady Step method

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Genetic
```
public Genetic()
```
    Creates a new instance of Genetic
- Method Detail
  - getLenghtPop
```
public int getLenghtPop()
```
    Methods to get the lenght of the population
    
    Returns:
    
    Length of the population
  - setLenghtPop
```
public void setLenghtPop(int value)
```
    Methods to set the lenght of the population
    
    Parameters:
    
    value - Length of the population
  - setMuNext
```
public void setMuNext(int value)
```
    Sets the value for indicating the position of the next mutation
    
    Parameters:
    
    value - Value of the variable Mu_next
  - getNEval
```
public int getNEval()
```
    Methods to get the number of evaluation to perform in an iteration of the GA
    
    Returns:
    
    Number of evaluations
  - setNEval
```
public void setNEval(int value)
```
    Methods to set the number of evaluation to perform in an iteration of the GA
    
    Parameters:
    
    value - Number of evaluations
  - getMinConf
```
public float getMinConf()
```
    Methods to get the value for the minimum confidence of the rules to be generated
    
    Returns:
    
    Minimum confidence
  - setMinConf
```
public void setMinConf(float value)
```
    Methods to set the value for the minimum confidence of the rules to be generated
    
    Parameters:
    
    value - Minimum confidence
  - getRulesRep
```
public java.lang.String getRulesRep()
```
    Gets the representation of the rules
    
    Returns:
    
    Representation of the rules
  - setRulesRep
```
public void setRulesRep(java.lang.String value)
```
    Sets the representation of the rules
    
    Parameters:
    
    value - Representation of the rules
  - getProbCross
```
public float getProbCross()
```
    Methods to get the value for the crossover probability
    
    Returns:
    
    Crossover probability
  - setProbCross
```
public void setProbCross(float value)
```
    Methods to set the value for the crossover probability
    
    Parameters:
    
    value - Crossover probability
  - getProbMut
```
public float getProbMut()
```
    Methods to get the value for the mutation probability
    
    Returns:
    
    Mutation probability
  - setProbMut
```
public void setProbMut(float value)
```
    Methods to set the value for the mutation probability
    
    Parameters:
    
    value - Mutation probability
  - getW1
```
public float getW1()
```
    Methods to get the value for the weight of the objective 1
    
    Returns:
    
    Weight of the objective 1
  - getW2
```
public float getW2()
```
    Methods to get the value for the weight of the objective 2
    
    Returns:
    
    Weight of the objective 2
  - getW3
```
public float getW3()
```
    Methods to get the value for the weight of the objective 3
    
    Returns:
    
    Weight of the objective 3
  - getW
```
public float getW(int pos)
```
    Methods to get the value for the weight of the objective in a position
    
    Parameters:
    
    pos - of the objective
    
    Returns:
    
    Weight of the objective
  - setW1
```
public void setW1(float value)
```
    Methods to set the value for the weight of the objective 1
    
    Parameters:
    
    value - Weight of the objective 1
  - setW2
```
public void setW2(float value)
```
    Methods to set the value for the weight of the objective 2
    
    Parameters:
    
    value - Weight of the objective 2
  - setW3
```
public void setW3(float value)
```
    Methods to set the value for the weight of the objective 3
    
    Parameters:
    
    value - Weight of the objective 3
  - getObj1
```
public java.lang.String getObj1()
```
    Methods to get the name of the quality measure as objective 1
    
    Returns:
    
    Quality measure of the objective 1
  - getObj2
```
public java.lang.String getObj2()
```
    Methods to get the name of the quality measure as objective 2
    
    Returns:
    
    Quality measure of the objective 2
  - getObj3
```
public java.lang.String getObj3()
```
    Methods to get the name of the quality measure as objective 3
    
    Returns:
    
    Quality measure of the objective 3
  - getObj
```
public java.lang.String getObj(int pos)
```
    Methods to get the name of the quality measure as objective in a position
    
    Parameters:
    
    pos - Position of the quality measure
    
    Returns:
    
    Quality measure of the objective
  - setObj1
```
public void setObj1(java.lang.String value)
```
    Methods to set the value for the quality measures as objective 1
    
    Parameters:
    
    value - Quality measure as objetive 1
  - setObj2
```
public void setObj2(java.lang.String value)
```
    Methods to set the value for the quality measures as objective 2
    
    Parameters:
    
    value - Quality measure as objetive 2
  - setObj3
```
public void setObj3(java.lang.String value)
```
    Methods to set the value for the quality measures as objective 3
    
    Parameters:
    
    value - Quality measure as objetive 3
  - getLSearch
```
public boolean getLSearch()
```
    Methods to get if local search must be performed
    
    Returns:
    
    Value of local search
  - setLSearch
```
public void setLSearch(boolean value)
```
    Methods to set if local search must be performed
    
    Parameters:
    
    value - Value of local search
  - getBestGuy
```
public int getBestGuy()
```
    Return the position of the best individual of the main population
    
    Returns:
    
    Position of the best individual
  - getQualityMeasures
```
public QualityMeasures getQualityMeasures(int pos,
                                          java.lang.String nFile)
```
    Get the measures of a single rule of the main population
    
    Parameters:
    
    pos - Position of the individual
    
    nFile - Name of the file to write the values
    
    Returns:
    
    the measures of a single rule of the main population
  - evalIndiv
```
public void evalIndiv(int pos,
                      Genetic AG,
                      TableVar Variables,
                      TableDat Examples,
                      boolean marcar)
```
    Evaluates an individual of the main population
    
    Parameters:
    
    pos - Position of the invidivual
    
    AG - Genetic algorithm object
    
    Variables - Structure of the Variables
    
    Examples - Structure of the Examples
    
    marcar - Indicates to mark the covered examples
  - getIndivCromCAN
```
public CromCAN getIndivCromCAN(int pos)
```
    Returns de hole chromosome of the selected individual
    
    Parameters:
    
    pos - Position of the individual
    
    Returns:
    
    Canonical chromosome of the individual
  - getIndivCromDNF
```
public CromDNF getIndivCromDNF(int pos)
```
    Returns de hole chromosome of the selected individual
    
    Parameters:
    
    pos - Position of the individual
    
    Returns:
    
    DNF chromosome of the individual
  - SelectCAN
```
public void SelectCAN(TableVar Variables)
```
    Applies the selection schema of the genetic algorithm
    
    Parameters:
    
    Variables - Structure of Variables
  - SelectDNF
```
public void SelectDNF(TableVar Variables)
```
    Applies the selection schema of the genetic algorithm
    
    Parameters:
    
    Variables - Structure of Variables
  - MultipointCrossoverCAN
```
public void MultipointCrossoverCAN(TableVar Variables)
```
    Cross operator for the genetic algorithm, where only cross the two better individuals
    
    Parameters:
    
    Variables - Structure of Variables
  - MultipointCrossoverDNF
```
public void MultipointCrossoverDNF(TableVar Variables)
```
    Cross operator for the genetic algorithm, where only cross the two better individuals
    
    Parameters:
    
    Variables - Structure of Variables
  - MutationCAN
```
public void MutationCAN(TableVar Variables)
```
    Applies the mutation operator. Uniform biased operator
    
    Parameters:
    
    Variables - Structure of Variables
  - MutationDNF
```
public void MutationDNF(TableVar Variables)
```
    Applies the mutation operator. Uniform biased operator
    
    Parameters:
    
    Variables - Structure of Variables
  - SteadyStepReproductionDNF
```
public void SteadyStepReproductionDNF(TableVar Variables)
```
    Uses a Steady Step method
    
    Parameters:
    
    Variables - Structure of Variables
  - SteadyStepReproductionCAN
```
public void SteadyStepReproductionCAN(TableVar Variables)
```
    Uses a Steady Step method
    
    Parameters:
    
    Variables - Structure of Variables
  - LocalImprovementCAN
```
public boolean LocalImprovementCAN(TableVar Variables,
                                   TableDat Examples)
```
    Locally improves the rule generated. This method locally optimizes on support.
    
    Parameters:
    
    Variables - Structure of Variables
    
    Examples - Structure of Examples
    
    Returns:
    
    If the improvement is performed
  - LocalImprovementDNF
```
public boolean LocalImprovementDNF(TableVar Variables,
                                   TableDat Examples)
```
    Locally improves the rule generated. This method locally optimizes on support.
    
    Parameters:
    
    Variables - Structure of Variables
    
    Examples - Structure of Examples
    
    Returns:
    
    If the improvement is performed
  - GeneticAlgorithm
```
public void GeneticAlgorithm(TableVar Variables,
                             TableDat Examples,
                             java.lang.String nFile)
```
    Composes the genetic algorithm applying the operators
    
    Parameters:
    
    Variables - Structure of Variables
    
    Examples - Structure of Examples
    
    nFile - File to write the process of the genetic algorithm

Class Genetic

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Genetic

Method Detail

getLenghtPop

setLenghtPop

setMuNext

getNEval

setNEval

getMinConf

setMinConf

getRulesRep

setRulesRep

getProbCross

setProbCross

getProbMut

setProbMut

getW1

getW2

getW3

getW

setW1

setW2

setW3

getObj1

getObj2

getObj3

getObj

setObj1

setObj2

setObj3

getLSearch

setLSearch

getBestGuy

getQualityMeasures

evalIndiv

getIndivCromCAN

getIndivCromDNF

SelectCAN

SelectDNF

MultipointCrossoverCAN

MultipointCrossoverDNF

MutationCAN

MutationDNF

SteadyStepReproductionDNF

SteadyStepReproductionCAN

LocalImprovementCAN

LocalImprovementDNF

GeneticAlgorithm