code: def create_polynom_logistic_regression_classifier(
      degree: int = 3, **kwargs_logistic_regression
  ) -> SklearnClassificationModel:
      return SklearnClassificationModel(
          make_pipeline(
              PolynomialFeatures(degree=degree, include_bias=False),
              LogisticRegression(**kwargs_logistic_regression),
          )
      )
  
imports: from abc import abstractmethod
  from typing import List
  import numpy
  import sklearn
  from packaging import version
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import PolynomialFeatures
  from dowhy.gcm.ml.prediction_model import PredictionModel
  from sklearn.ensemble import AdaBoostClassifier, ExtraTreesClassifier, HistGradientBoostingClassifier, RandomForestClassifier
  from sklearn.gaussian_process import GaussianProcessClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.naive_bayes import GaussianNB
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.svm import SVC
  from dowhy.gcm.ml.regression import SklearnRegressionModel
  from dowhy.gcm.util.general import auto_apply_encoders, shape_into_2d
label_desc: Use image node_id 10 for calling a global function with example usage: create_polynom_logistic_regression_classifier(degree) and returns: SklearnClassificationModel