Space
- class sklearn_genetic.space.Categorical(choices: Optional[list] = None, priors: Optional[list] = None, distribution: str = 'choice')[source]
class for hyperparameters search space of categorical values
- Parameters
- choices: list, default=None
List with all the possible values of the hyperparameter.
- priors: int, default=None
List with the probability of sampling each element of the “choices”, if not set gives equals probability.
- distribution: str, default=’choice’
Distribution to sample initial population and mutation values, currently only supports “choice”.
- class sklearn_genetic.space.Continuous(lower: Optional[float] = None, upper: Optional[float] = None, distribution: str = 'uniform')[source]
class for hyperparameters search space of real values
- Parameters
- lowerint, default=None
Lower bound of the possible values of the hyperparameter.
- upperint, default=None
Upper bound of the possible values of the hyperparameter.
- distribution{‘uniform’, ‘log-uniform’}, default=’uniform’
Distribution to sample initial population and mutation values.
- class sklearn_genetic.space.Integer(lower: Optional[int] = None, upper: Optional[int] = None, distribution: str = 'uniform')[source]
class for hyperparameters search space of integer values
- Parameters
- lowerint, default=None
Lower bound of the possible values of the hyperparameter.
- upperint, default=None
Upper bound of the possible values of the hyperparameter.
- distributionstr, default=”uniform”
Distribution to sample initial population and mutation values, currently only supports ‘uniform’.
- class sklearn_genetic.space.Space(param_grid: Optional[dict] = None)[source]
Search space for all the models hyperparameters
- Parameters
- param_grid: dict, default=None
Grid with the parameters to tune, expects keys a valid name of hyperparameter based on the estimator selected and as values one of
Integer
,Categorical
Continuous
classes
- property dimensions
- Returns
- The number of hyperparameters defined in the param_grid
- property parameters
- Returns
- A list with all the names of the hyperparametes in the param_Grid