Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
Modifier and Type | Method and Description |
---|---|
private AggarwalYuEvolutionary.Individuum |
AggarwalYuEvolutionary.EvolutionarySearch.combineRecursive(ArrayList<Integer> r,
int i,
int[] current,
AggarwalYuEvolutionary.Individuum parent1,
AggarwalYuEvolutionary.Individuum parent2)
Recursive method to build all possible gene combinations using positions
in r.
|
private AggarwalYuEvolutionary.Individuum |
AggarwalYuEvolutionary.EvolutionarySearch.makeIndividuum(int[] gene)
Make a new individuum helper, computing sparsity=fitness
|
static AggarwalYuEvolutionary.Individuum |
AggarwalYuEvolutionary.Individuum.nullIndividuum(int dim)
Create a "null" individuum (full space).
|
Modifier and Type | Method and Description |
---|---|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.crossoverOptimized(ArrayList<AggarwalYuEvolutionary.Individuum> population)
method implements the crossover algorithm
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.initialPopulation(int popsize)
Produce an initial (random) population.
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.mutation(ArrayList<AggarwalYuEvolutionary.Individuum> population,
double perc1,
double perc2)
Apply the mutation alogrithm.
|
private Pair<AggarwalYuEvolutionary.Individuum,AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.recombineOptimized(AggarwalYuEvolutionary.Individuum parent1,
AggarwalYuEvolutionary.Individuum parent2)
Recombination method.
|
private Pair<AggarwalYuEvolutionary.Individuum,AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.recombineOptimized(AggarwalYuEvolutionary.Individuum parent1,
AggarwalYuEvolutionary.Individuum parent2)
Recombination method.
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.rouletteRankSelection(ArrayList<AggarwalYuEvolutionary.Individuum> population)
Select surviving individuums weighted by rank.
|
Iterable<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.run() |
Modifier and Type | Method and Description |
---|---|
private AggarwalYuEvolutionary.Individuum |
AggarwalYuEvolutionary.EvolutionarySearch.combineRecursive(ArrayList<Integer> r,
int i,
int[] current,
AggarwalYuEvolutionary.Individuum parent1,
AggarwalYuEvolutionary.Individuum parent2)
Recursive method to build all possible gene combinations using positions
in r.
|
private Pair<AggarwalYuEvolutionary.Individuum,AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.recombineOptimized(AggarwalYuEvolutionary.Individuum parent1,
AggarwalYuEvolutionary.Individuum parent2)
Recombination method.
|
Modifier and Type | Method and Description |
---|---|
private boolean |
AggarwalYuEvolutionary.EvolutionarySearch.checkConvergence(Collection<AggarwalYuEvolutionary.Individuum> pop)
check the termination criterion.
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.crossoverOptimized(ArrayList<AggarwalYuEvolutionary.Individuum> population)
method implements the crossover algorithm
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.mutation(ArrayList<AggarwalYuEvolutionary.Individuum> population,
double perc1,
double perc2)
Apply the mutation alogrithm.
|
private ArrayList<AggarwalYuEvolutionary.Individuum> |
AggarwalYuEvolutionary.EvolutionarySearch.rouletteRankSelection(ArrayList<AggarwalYuEvolutionary.Individuum> population)
Select surviving individuums weighted by rank.
|