Add support for dict-like parameters

[MarekWadinger]

Complete Description of the Issue

As a software developer, I want to tune dict-like parameters of ML model to improve its ability to generalize. This is a default behavior of parameter searching algorithms in sklearn (e.g., GridSearchCV ). Though able to use same API, NatureInspiredSearchCV raises an TypeError.

Simplest Possible Self-Contained Example Showing the Bug

from sklearn.datasets import make_classification
from sklearn.tree import DecisionTreeClassifier as DTC
from sklearn_nature_inspired_algorithms.model_selection import\
    NatureInspiredSearchCV as NIS_CV

X, y = make_classification()

tree = DTC(random_state=0)

param_grid = {'class_weight':
              [{False: 1, True: 2},
               {False: 1, True: 1}]}

sh = NIS_CV(tree, param_grid, scoring='f1_macro').fit(X, y)

Full Backtrace of Exception

Exception has occurred: TypeError

Exception has occurred: TypeError unhashable type: 'dict' File "./Sklearn-Nature-Inspired-Search/sklearn_nature_inspired_algorithms/model_selection/_parameter_search.py", line 23, in get_cached_score if cache_key in self.cache: File "./Sklearn-Nature-Inspired-Search/sklearn_nature_inspired_algorithms/model_selection/_parameter_search.py", line 35, in _evaluate score = self.get_cached_score(params) File "./Sklearn-Nature-Inspired-Search/sklearn_nature_inspired_algorithms/model_selection/_stagnation_stopping_task.py", line 40, in eval x_f = super().eval(A) File "./Sklearn-Nature-Inspired-Search/sklearn_nature_inspired_algorithms/model_selection/nature_inspired_search_cv.py", line 47, in _run_search self.__algorithm.run(task=task) File "./Sklearn-Nature-Inspired-Search/sklearn_nature_inspired_algorithms/model_selection/nature_inspired_search_cv.py", line 19, in fit return super().fit(X, y, groups=groups, **fit_params) File "./RnD/Similarity/bug_nia.py", line 15, in sh = NIS_CV(tree, param_grid, scoring='f1_macro').fit(X, y) TypeError: unhashable type: 'dict'