GeneticWeightLearning

java.lang.Object
- Core.BaseLearners.LearningAttributeWeights.LearningAttributeWeights
- - Core.BaseLearners.LearningAttributeWeights.GeneticWeightLearning

```
public class GeneticWeightLearning
extends LearningAttributeWeights
```
Implements a Genetic Algorithm Optimization method to optimize the weight of the attributes. This algorithm iterates through generations of a given amount of chromosomes (50 as default) for a given amount of time (30s as default), simulating a process of evolution and natural selection through chromosome pairing and locus crossover and mutation, with the following selection of the fittest individuals to remain in the population for the next iteration. The optimization of the weights is performed over the whole case base. It may perform an over-fitting of the weights.

Field Summary
- Fields inherited from class Core.BaseLearners.LearningAttributeWeights.LearningAttributeWeights
  path

Constructors
Constructor and Description
`GeneticWeightLearning()` Constructor to accept default parameter values
`GeneticWeightLearning(int nIndiv, float crossoverProb, float mutationProb, float mutationCoef, long executionTimeInSeconds)` Constructor to set custom parameter values

Methods
Modifier and Type	Method and Description
`Attribute[]`	`learn(CBR cbr, Attribute[] attributes)` Mètode de aprenentatge de pesos que modifica el pes dels atributs de la Population train en funció de la Population de test

Methods inherited from class Core.BaseLearners.LearningAttributeWeights.LearningAttributeWeights
addIgnoredWeights, learnWeights

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

Class GeneticWeightLearning