Sklearn-nature-inspired-algorithms

The nature-inspired search can be run multiple times, this will provide more stable results. Helper visualization functions were updated to show multiple runs/select run to show.

- new algorithms: Hybrid Bat Algorithm, Hybrid Self Adapting Bat Algorithm
- changed default option values for `NatureInspiredSearchCV`, the new defaults are:
- `algorithm` = `hba`
- `population_size` = `50`
- `max_n_gen` = `100`
- `max_stagnating_gen` = `20`

- bug fixes

- added support to select metric (`min`, `max`, `median`, `mean`) in `score_by_generation_lineplot`

- changed default option values for `NatureInspiredSearchCV`, the new defaults are:
- `algorithm` = `ba`
- `population_size` = `15`
- `max_n_gen` = `25`
- `max_stagnating_gen` = `2`
- new helper methods `score_by_generation_violinplot`, `score_by_generation_lineplot` for plotting the search progress
python
from sklearn_nature_inspired_algorithms.model_selection import NatureInspiredSearchCV
from sklearn_nature_inspired_algorithms.helpers import score_by_generation_violinplot

nia_search = NatureInspiredSearchCV(clf, param_grid)

score_by_generation_violinplot(nia_search)