code: def get_fast_regressors():
      """Get a list of very fast regressors.
  
      Returns
      -------
      fast_regressors : list of sklearn estimators
          List of regression models that can be fitted and evaluated very
          quickly.
      """
      return [
          DummyRegressor(),
          DecisionTreeRegressor(max_depth=1),
          DecisionTreeRegressor(max_leaf_nodes=8),
          DecisionTreeRegressor(max_leaf_nodes=16),
          DecisionTreeRegressor(max_leaf_nodes=32),
          DecisionTreeRegressor(max_depth=5),
          Ridge(alpha=10),
          Lasso(alpha=10),
      ]
  
file_path: dabl/dabl/pipelines.py
imports: from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.naive_bayes import GaussianNB, MultinomialNB
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression, Ridge, Lasso
  from .portfolios.portfolio_base import portfolio_base
  from .portfolios.portfolio_mixed import portfolio_mixed
  from .portfolios.portfolio_hgb import portfolio_hgb
  from .portfolios.portfolio_svc import portfolio_svc
  from .portfolios.portfolio_rf import portfolio_rf
  from .portfolios.portfolio_lr import portfolio_lr
label_desc: Use image node_id 2 for calling a global function with example usage: get_fast_regressors() and returns: list