Plots¶
- sklearn_genetic.plots.plot_fitness_evolution(estimator, metric='fitness')[source]¶
- Parameters
- estimator: estimator object
A fitted estimator from
GASearchCV- metric: {“fitness”, “fitness_std”, “fitness_max”, “fitness_min”}, default=”fitness”
Logged metric into the estimator history to plot
- Returns
- Lines plot with the fitness value in each generation
- sklearn_genetic.plots.plot_search_space(estimator, height=2, s=25, features: Optional[list] = None)[source]¶
- Parameters
- estimator: estimator object
A fitted estimator from
GASearchCV- height: float, default=2
Height of each facet
- s: float, default=5
Size of the markers in scatter plot
- features: list, default=None
Subset of features to plot, if
Noneit plots all the features by default
- Returns
- Pair plot of the used hyperparameters during the search