class_docstr: Logistic Regression oneDAL implementation.
class_docstr_tok: ["Logistic","Regression","oneDAL","implementation","."]
code: def predict(self, X, queue=None):
      y = super()._predict(
          X, _backend.logistic_regression.classification, queue
      )
      return y
  
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 LogisticRegression obj's underlying member method code with example usage: obj.predict(X, queue) and returns: y