Uses of Class
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum

Packages that use AggarwalYuEvolutionary.Individuum

Package	Description
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods.

Uses of AggarwalYuEvolutionary.Individuum in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace that return AggarwalYuEvolutionary.Individuum

Modifier and Type	Method and Description
private AggarwalYuEvolutionary.Individuum	AggarwalYuEvolutionary.EvolutionarySearch.combineRecursive(gnu.trove.list.array.TIntArrayList r, int i, short[] 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(short[] gene) Make a new individuum helper, computing sparsity=fitness
static AggarwalYuEvolutionary.Individuum	AggarwalYuEvolutionary.Individuum.nullIndividuum(int dim) Create a "null" individuum (full space).

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace that return types with arguments of type AggarwalYuEvolutionary.Individuum

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 algorithm.
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.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with parameters of type AggarwalYuEvolutionary.Individuum

Modifier and Type	Method and Description
private AggarwalYuEvolutionary.Individuum	AggarwalYuEvolutionary.EvolutionarySearch.combineRecursive(gnu.trove.list.array.TIntArrayList r, int i, short[] current, AggarwalYuEvolutionary.Individuum parent1, AggarwalYuEvolutionary.Individuum parent2) Recursive method to build all possible gene combinations using positions in r.
int	AggarwalYuEvolutionary.Individuum.compareTo(AggarwalYuEvolutionary.Individuum o)
private Pair<AggarwalYuEvolutionary.Individuum,AggarwalYuEvolutionary.Individuum>	AggarwalYuEvolutionary.EvolutionarySearch.recombineOptimized(AggarwalYuEvolutionary.Individuum parent1, AggarwalYuEvolutionary.Individuum parent2) Recombination method.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with type arguments of type AggarwalYuEvolutionary.Individuum

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 algorithm.
private ArrayList<AggarwalYuEvolutionary.Individuum>	AggarwalYuEvolutionary.EvolutionarySearch.rouletteRankSelection(ArrayList<AggarwalYuEvolutionary.Individuum> population) Select surviving individuums weighted by rank.