code: def is_linear_model(model_names):
      linear_models = set(
          [
              "RANSACRegressor",
              "LinearRegression",
              "Ridge",
              "Lasso",
              "ElasticNet",
              "LassoLars",
              "OrthogonalMatchingPursuit",
              "BayesianRidge",
              "ARDRegression",
              "SGDRegressor",
              "PassiveAggressiveRegressor",
              "LogisticRegression",
              "RidgeClassifier",
              "SGDClassifier",
              "Perceptron",
              "PassiveAggressiveClassifier",
          ]
      )
  
      if len(linear_models & (set(model_names))) > 0:
          return True
      else:
          return False
  
imports: import csv
  import datetime
  import numbers
  import os
  import pkg_resources
  import numpy
  import pandas
  import scipy
  from sklearn.datasets import load_boston
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils.metaestimators import if_delegate_has_method
  from sklearn.utils import column_or_1d
  from auto_ml._version import __version__
label_desc: Use image node_id 1 for calling a global function with example usage: is_linear_model(model_names) and returns: True, False