public class multipopulation
extends java.lang.Object
implements java.lang.Cloneable
Modifier and Type | Method and Description |
---|---|
void |
Assessment(int i,
double[] valor) |
void |
Better(int nclases,
int[] better,
Int_t nbetter) |
int |
ClassIndividual(int ind) |
java.lang.Object |
clone() |
void |
Code(int i,
genetcode code)
Returns in "code" the genetic code of the individual "i"
|
int |
Elite() |
void |
GenerationalCrossover()
Generational crossover operator
|
boolean |
Higher(double[] v1,
double[] v2,
int n) |
void |
InitialPopulation(double[][] I,
int rango,
int n_items,
int consecuente,
int[][] sujetos,
int n_var,
int[] n_etiquetas_variable)
Generates an initial population
|
double |
MeanFitness() |
boolean |
Modified(int i) |
int |
N_individuals() |
int |
N_Val() |
void |
Paint() |
void |
Paint(int i) |
void |
PaintFitness_Stationary(int i) |
void |
PaintFitness(int i) |
void |
PaintFitnessInFile(int i) |
void |
PaintIndividual(int i) |
void |
Put_NotModified() |
void |
PutCode(int i,
genetcode code) |
void |
PutModified(int i) |
void |
Selection()
Selection operator
|
void |
Sort()
Sorts the individuals according to their fitness values
|
char[] |
Subpopulation_Binary(int subpoblacion,
int individuo,
Int_t tama)
Returns the binary subpopulation of the individual "individuo"
|
int[] |
Subpopulation_Integer(int subpoblacion,
int individuo,
Int_t tama)
Returns the integer subpopulation of the individual "individuo"
|
double[] |
Subpopulation_Real(int subpoblacion,
int individuo,
Int_t tama)
Returns the real subpopulation of the individual "individuo"
|
void |
Swap_bool(boolean[] v,
int i,
int j) |
void |
Swap_double(double[] v,
int i,
int j) |
void |
Swap_int(int[] v,
int i,
int j) |
void |
Swap(int i,
int j) |
void |
UniformMutation()
Uniform mutation operator
|
double |
ValueFitness(int i) |
double |
ValueFitness(int i,
int j) |
int |
ValueIndividual(int population,
int ind) |
public java.lang.Object clone()
clone
in class java.lang.Object
public void Swap(int i, int j)
public void Swap_int(int[] v, int i, int j)
public void Swap_double(double[] v, int i, int j)
public void Swap_bool(boolean[] v, int i, int j)
public void Sort()
Sorts the individuals according to their fitness values
public int ClassIndividual(int ind)
public int ValueIndividual(int population, int ind)
public char[] Subpopulation_Binary(int subpoblacion, int individuo, Int_t tama)
Returns the binary subpopulation of the individual "individuo"
subpoblacion
- int The selected subpopulationindividuo
- int The selected individualtama
- Int_t Size of the subpopulationpublic int[] Subpopulation_Integer(int subpoblacion, int individuo, Int_t tama)
Returns the integer subpopulation of the individual "individuo"
subpoblacion
- int The selected subpopulationindividuo
- int The selected individualtama
- Int_t Size of the subpopulationpublic double[] Subpopulation_Real(int subpoblacion, int individuo, Int_t tama)
Returns the real subpopulation of the individual "individuo"
subpoblacion
- int The selected subpopulationindividuo
- int The selected individualtama
- Int_t Size of the subpopulationpublic void Better(int nclases, int[] better, Int_t nbetter)
public boolean Higher(double[] v1, double[] v2, int n)
public void Paint(int i)
public void Paint()
public double MeanFitness()
public void PaintFitness(int i)
public void PaintFitnessInFile(int i) throws java.io.IOException
java.io.IOException
public void PaintFitness_Stationary(int i)
public void PaintIndividual(int i)
public int N_individuals()
public int Elite()
public int N_Val()
public void Code(int i, genetcode code)
Returns in "code" the genetic code of the individual "i"
i
- int The selected individualcode
- genetcode The structure storing the genetic codepublic void PutCode(int i, genetcode code)
public boolean Modified(int i)
public void PutModified(int i)
public void Assessment(int i, double[] valor)
public void InitialPopulation(double[][] I, int rango, int n_items, int consecuente, int[][] sujetos, int n_var, int[] n_etiquetas_variable)
Generates an initial population
I
- double[][] Information measuresrango
- int Number of classesn_items
- int Number of examplesconsecuente
- int The selected classsujetos
- int[][] The individuals found according to the examplesn_var
- int Number of antecedent variablesn_etiquetas_variable
- int[] Information related to the domain of each variablepublic void Put_NotModified()
public void UniformMutation()
Uniform mutation operator
public void GenerationalCrossover()
Generational crossover operator
public void Selection()
Selection operator
public double ValueFitness(int i)
public double ValueFitness(int i, int j)