Algorithms
|
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py |
|
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py |
|
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py |
- sklearn_genetic.algorithms.eaMuCommaLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, stats=None, halloffame=None, callbacks=None, verbose=True, estimator=None)[source]
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py
This is the \((\mu~,~\lambda)\) evolutionary algorithm.
- population: A list of individuals.
Population resulting of the iteration process.
- toolbox: A
Toolbox
Contains the evolution operators.
- mu: int, default=None,
The number of individuals to select for the next generation.
- lambda_: int, default=None
The number of children to produce at each generation.
- cxpb: float, default=None
The probability that an offspring is produced by crossover.
- mutpb: float, default=None
The probability that an offspring is produced by mutation.
- ngen: int, default=None
The number of generation.
- stats: A
Statistics
Object that is updated inplace, optional.
- halloffame: A
HallOfFame
Object that will contain the best individuals, optional.
- callbacks: list or Callable
One or a list of the
callbacks
methods available in the package.- verbose: bool, default=True
Whether or not to log the statistics.
- estimator:
GASearchCV
, default = None Estimator that is being optimized
- Returns
- pop: list
The final population.
- log: Logbook
Statistics of the evolution.
- n_gen: int
Number of generations used.
- sklearn_genetic.algorithms.eaMuPlusLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, stats=None, halloffame=None, callbacks=None, verbose=True, estimator=None)[source]
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py
This is the \((\mu + \lambda)\) evolutionary algorithm.
- population: A list of individuals.
Population resulting of the iteration process.
- toolbox: A
Toolbox
Contains the evolution operators.
- mu: int, default=None
The number of individuals to select for the next generation.
- lambda_: int, default=None
The number of children to produce at each generation.
- cxpb: float, default=None
The probability that an offspring is produced by crossover.
- mutpb: float, default=None
The probability that an offspring is produced by mutation.
- ngen: int, default=None
The number of generation.
- stats: A
Statistics
Object that is updated inplace, optional.
- halloffame: A
HallOfFame
Object that will contain the best individuals, optional.
- callbacks: list or Callable
One or a list of the
callbacks
methods available in the package.- verbose: bool, default=True
Whether or not to log the statistics.
- estimator:
GASearchCV
, default = None Estimator that is being optimized
- Returns
- pop: list
The final population.
- log: Logbook
Statistics of the evolution.
- n_gen: int
Number of generations used.
- sklearn_genetic.algorithms.eaSimple(population, toolbox, cxpb, mutpb, ngen, stats=None, halloffame=None, callbacks=None, verbose=True, estimator=None)[source]
The base implementation is directly taken from: https://github.com/DEAP/deap/blob/master/deap/algorithms.py
This algorithm reproduce the simplest evolutionary algorithm as presented in chapter 7 of Back2000.
- population: A list of individuals.
Population resulting of the iteration process.
- toolbox: A
Toolbox
Contains the evolution operators.
- cxpb: float, default=None
The probability of mating two individuals.
- mutpb: float, default=None
The probability of mutating an individual.
- ngen: int, default=None
The number of generation.
- stats: A
Statistics
Object that is updated inplace, optional.
- halloffame: A
HallOfFame
Object that will contain the best individuals, optional.
- callbacks: list or callable
One or a list of the
callbacks
methods available in the package.- verbose: bool, default=True
Whether or not to log the statistics.
- estimator:
GASearchCV
, default = None Estimator that is being optimized
- Returns
- pop: list
The final population.
- log: Logbook
Statistics of the evolution.
- n_gen: int
Number of generations used.