code: def get_any_classifiers(portfolio="baseline"):
      """Return a portfolio of classifiers.
  
      Returns
      -------
      classifiers : list of sklearn estimators
          List of classification models.
      """
      baseline = portfolio_base()
      mixed = portfolio_mixed()
      hgb = portfolio_hgb()
      svc = portfolio_svc()
      rf = portfolio_rf()
      lr = portfolio_lr()
  
      portfolios = {
          "baseline": baseline,
          "mixed": mixed,
          "svc": svc,
          "hgb": hgb,
          "rf": rf,
          "lr": lr,
      }
  
      return portfolios[portfolio]
  
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 3 for calling a global function with example usage: get_any_classifiers(portfolio) and returns: portfolios