code: def _get_onedal_params(self, dtype=np.float32):
      intercept = "intercept|" if self.fit_intercept else ""
      return {
          "fptype": "float" if dtype == np.float32 else "double",
          "method": self.algorithm,
          "intercept": self.fit_intercept,
          "tol": self.tol,
          "max_iter": self.max_iter,
          "C": self.C,
          "optimizer": self.solver,
          "result_option": (
              intercept + "coefficients|iterations_count"
          ),
      }
  
imports: from abc import ABCMeta, abstractmethod
  from numbers import Number
  import numpy
  from sklearn.base import BaseEstimator
  from daal4py.sklearn._utils import get_dtype, make2d
  from onedal import _backend
  from ..common._estimator_checks import _check_is_fitted
  from ..common._mixin import ClassifierMixin
  from ..common._policy import _get_policy
  from ..datatypes import _convert_to_supported, from_table, to_table
  from ..utils import _check_array, _check_n_features, _check_X_y, _num_features, _type_of_target
label_desc: Use image node_id 3 for calling the BaseLogisticRegression obj's underlying member method code with example usage: obj._get_onedal_params(dtype) and returns: dict