[BUG]: tuning `'ransac'` model does not work

### pycaret version checks

- [X] I have checked that this issue has not already been reported [here](https://github.com/pycaret/pycaret/issues).

- [X] I have confirmed this bug exists on the [latest version](https://github.com/pycaret/pycaret/releases) of pycaret.

- [X] I have confirmed this bug exists on the master branch of pycaret (pip install -U git+https://github.com/pycaret/pycaret.git@master).


### Issue Description

- the 'loss' parameter of RANSACRegressor is not set correctly
- for example `absolute_loss` is set when optimizing against `"R2"`/Default, and `squared_loss` when optimizing against `"RMSE"`

### Reproducible Example

```python
from pycaret.datasets import get_data
from pycaret.regression import RegressionExperiment

data = get_data("insurance")

sort_metric = "RMSE"

exp = RegressionExperiment()
exp.setup(
    data=data,
    target="charges",
    transform_target=True,
    transformation=True,
)
ransac = exp.create_model("ransac")
```

and then tuning with
```python
tuned = exp.tune_model(
    estimator=ransac,
    choose_better=True,
    optimize="RMSE",
)
```
produces `sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'absolute_loss' instead.`

or
```python
tuned = exp.tune_model(
    estimator=ransac,
    choose_better=True,
)
```
produces `sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'squared_loss' instead.`



### Expected Behavior

tuning with 'ransac' estimator works irrespective of quality of the model; just working

### Actual Results

```python-traceback
{
	"name": "ValueError",
	"message": "
All the 100 fits failed.
It is very likely that your model is misconfigured.
You can try to debug the error by setting error_score='raise'.

Below are more details about the failures:
--------------------------------------------------------------------------------
26 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'absolute_loss' instead.

--------------------------------------------------------------------------------
24 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'squared_error', 'absolute_error'} or a callable. Got 'absolute_loss' instead.

--------------------------------------------------------------------------------
13 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'squared_loss' instead.

--------------------------------------------------------------------------------
37 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'squared_error', 'absolute_error'} or a callable. Got 'squared_loss' instead.
",
	"stack": "---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[13], line 16
      9 exp.setup(
     10     data=data,
     11     target=\"charges\",
     12     transform_target=True,
     13     transformation=True,
     14 )
     15 ransac = exp.create_model(\"ransac\")
---> 16 tuned = exp.tune_model(
     17     estimator=ransac,
     18     choose_better=True,
     19     optimize=sort_metric,
     20 )

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/regression/oop.py:1499, in RegressionExperiment.tune_model(self, estimator, fold, round, n_iter, custom_grid, optimize, custom_scorer, search_library, search_algorithm, early_stopping, early_stopping_max_iters, choose_better, fit_kwargs, groups, return_tuner, verbose, tuner_verbose, return_train_score, **kwargs)
   1307 def tune_model(
   1308     self,
   1309     estimator,
   (...)
   1327     **kwargs,
   1328 ):
   1329     \"\"\"
   1330     This function tunes the hyperparameters of a given estimator. The output of
   1331     this function is a score grid with CV scores by fold of the best selected
   (...)
   1496 
   1497     \"\"\"
-> 1499     return super().tune_model(
   1500         estimator=estimator,
   1501         fold=fold,
   1502         round=round,
   1503         n_iter=n_iter,
   1504         custom_grid=custom_grid,
   1505         optimize=optimize,
   1506         custom_scorer=custom_scorer,
   1507         search_library=search_library,
   1508         search_algorithm=search_algorithm,
   1509         early_stopping=early_stopping,
   1510         early_stopping_max_iters=early_stopping_max_iters,
   1511         choose_better=choose_better,
   1512         fit_kwargs=fit_kwargs,
   1513         groups=groups,
   1514         return_tuner=return_tuner,
   1515         verbose=verbose,
   1516         tuner_verbose=tuner_verbose,
   1517         return_train_score=return_train_score,
   1518         **kwargs,
   1519     )

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pycaret_experiment/supervised_experiment.py:2672, in _SupervisedExperiment.tune_model(self, estimator, fold, round, n_iter, custom_grid, optimize, custom_scorer, search_library, search_algorithm, early_stopping, early_stopping_max_iters, choose_better, fit_kwargs, groups, return_tuner, verbose, tuner_verbose, return_train_score, **kwargs)
   2664     with patch(
   2665         \"sklearn.model_selection._search.sample_without_replacement\",
   2666         pycaret.internal.patches.sklearn._mp_sample_without_replacement,
   2667     ):
   2668         with patch(
   2669             \"sklearn.model_selection._search.ParameterGrid.__getitem__\",
   2670             pycaret.internal.patches.sklearn._mp_ParameterGrid_getitem,
   2671         ):
-> 2672             model_grid.fit(data_X, data_y, groups=groups, **fit_kwargs)
   2673 else:
   2674     model_grid.fit(data_X, data_y, groups=groups, **fit_kwargs)

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_search.py:874, in BaseSearchCV.fit(self, X, y, groups, **fit_params)
    868     results = self._format_results(
    869         all_candidate_params, n_splits, all_out, all_more_results
    870     )
    872     return results
--> 874 self._run_search(evaluate_candidates)
    876 # multimetric is determined here because in the case of a callable
    877 # self.scoring the return type is only known after calling
    878 first_test_score = all_out[0][\"test_scores\"]

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_search.py:1768, in RandomizedSearchCV._run_search(self, evaluate_candidates)
   1766 def _run_search(self, evaluate_candidates):
   1767     \"\"\"Search n_iter candidates from param_distributions\"\"\"
-> 1768     evaluate_candidates(
   1769         ParameterSampler(
   1770             self.param_distributions, self.n_iter, random_state=self.random_state
   1771         )
   1772     )

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_search.py:851, in BaseSearchCV.fit.<locals>.evaluate_candidates(candidate_params, cv, more_results)
    844 elif len(out) != n_candidates * n_splits:
    845     raise ValueError(
    846         \"cv.split and cv.get_n_splits returned \"
    847         \"inconsistent results. Expected {} \"
    848         \"splits, got {}\".format(n_splits, len(out) // n_candidates)
    849     )
--> 851 _warn_or_raise_about_fit_failures(out, self.error_score)
    853 # For callable self.scoring, the return type is only know after
    854 # calling. If the return type is a dictionary, the error scores
    855 # can now be inserted with the correct key. The type checking
    856 # of out will be done in `_insert_error_scores`.
    857 if callable(self.scoring):

File /workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py:367, in _warn_or_raise_about_fit_failures(results, error_score)
    360 if num_failed_fits == num_fits:
    361     all_fits_failed_message = (
    362         f\"\
All the {num_fits} fits failed.\
\"
    363         \"It is very likely that your model is misconfigured.\
\"
    364         \"You can try to debug the error by setting error_score='raise'.\
\
\"
    365         f\"Below are more details about the failures:\
{fit_errors_summary}\"
    366     )
--> 367     raise ValueError(all_fits_failed_message)
    369 else:
    370     some_fits_failed_message = (
    371         f\"\
{num_failed_fits} fits failed out of a total of {num_fits}.\
\"
    372         \"The score on these train-test partitions for these parameters\"
   (...)
    376         f\"Below are more details about the failures:\
{fit_errors_summary}\"
    377     )

ValueError: 
All the 100 fits failed.
It is very likely that your model is misconfigured.
You can try to debug the error by setting error_score='raise'.

Below are more details about the failures:
--------------------------------------------------------------------------------
26 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'absolute_loss' instead.

--------------------------------------------------------------------------------
24 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'squared_error', 'absolute_error'} or a callable. Got 'absolute_loss' instead.

--------------------------------------------------------------------------------
13 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'absolute_error', 'squared_error'} or a callable. Got 'squared_loss' instead.

--------------------------------------------------------------------------------
37 fits failed with the following error:
Traceback (most recent call last):
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 275, in fit
    fitted_estimator = self._memory_fit(
                       ^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/joblib/memory.py\", line 353, in __call__
    return self.func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/pycaret/internal/pipeline.py\", line 68, in _fit_one
    transformer.fit(*args, **fit_params)
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/linear_model/_ransac.py\", line 330, in fit
    self._validate_params()
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/base.py\", line 600, in _validate_params
    validate_parameter_constraints(
  File \"/workspaces/bebefam-exploration/.venv/lib/python3.11/site-packages/sklearn/utils/_param_validation.py\", line 97, in validate_parameter_constraints
    raise InvalidParameterError(
sklearn.utils._param_validation.InvalidParameterError: The 'loss' parameter of RANSACRegressor must be a str among {'squared_error', 'absolute_error'} or a callable. Got 'squared_loss' instead.
"
}
```


### Installed Versions

<details>
>>> from pycaret import show_versions; show_versions()

System:
    python: 3.11.7 (main, Dec  5 2023, 18:55:16) [GCC 12.2.0]
executable: /workspaces/bebefam-exploration/.venv/bin/python
   machine: Linux-6.5.0-14-generic-x86_64-with-glibc2.36

PyCaret required dependencies:
                 pip: 23.3.2
          setuptools: 69.0.3
             pycaret: 3.2.0
             IPython: 8.20.0
          ipywidgets: 8.1.1
                tqdm: 4.66.1
               numpy: 1.25.2
              pandas: 1.5.3
              jinja2: 3.1.2
               scipy: 1.10.1
              joblib: 1.3.2
             sklearn: 1.2.2
                pyod: 1.1.2
            imblearn: 0.11.0
   category_encoders: 2.6.3
            lightgbm: 4.2.0
               numba: 0.58.1
            requests: 2.31.0
          matplotlib: 3.6.0
          scikitplot: 0.3.7
         yellowbrick: 1.5
              plotly: 5.18.0
    plotly-resampler: Not installed
             kaleido: 0.2.1
           schemdraw: 0.15
         statsmodels: 0.14.1
              sktime: 0.21.1
               tbats: 1.1.3
            pmdarima: 2.0.4
              psutil: 5.9.7
          markupsafe: 2.1.3
             pickle5: Not installed
         cloudpickle: 3.0.0
         deprecation: 2.1.0
              xxhash: 3.4.1
           wurlitzer: 3.0.3

PyCaret optional dependencies:
                shap: 0.44.0
           interpret: Not installed
                umap: Not installed
     ydata_profiling: Not installed
  explainerdashboard: Not installed
             autoviz: Not installed
           fairlearn: Not installed
          deepchecks: Not installed
             xgboost: 2.0.3
            catboost: 1.2.2
              kmodes: 0.12.2
             mlxtend: 0.23.0
       statsforecast: 1.5.0
        tune_sklearn: Not installed
                 ray: Not installed
            hyperopt: Not installed
              optuna: Not installed
               skopt: Not installed
              mlflow: 1.27.0
              gradio: 3.50.2
             fastapi: 0.104.1
             uvicorn: 0.25.0
              m2cgen: 0.10.0
           evidently: 0.2.8
               fugue: 0.8.7
           streamlit: Not installed
             prophet: Not installed
</details>


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[BUG]: tuning `'ransac'` model does not work #3894

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[BUG]: tuning 'ransac' model does not work #3894

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[BUG]: tuning `'ransac'` model does not work #3894