code: def train_basic_multilabel_classifier(df_twitter_train):
      column_descriptions = {
          "airline_sentiment": "output",
          "airline": "categorical",
          "text": "ignore",
          "tweet_location": "categorical",
          "user_timezone": "categorical",
          "tweet_created": "date",
      }
  
      ml_predictor = Predictor(
          type_of_estimator="classifier",
          column_descriptions=column_descriptions,
      )
      ml_predictor.train(df_twitter_train)
  
      return ml_predictor
  
file_path: auto_ml/tests/advanced_tests/utils_testing.py
imports: import sys, os
  import pandas
  from sklearn.datasets import load_boston
  from sklearn.metrics import brier_score_loss, mean_squared_error
  from sklearn.model_selection import train_test_split
  from auto_ml import Predictor
label_desc: Use image node_id 8 for calling a global function with example usage: train_basic_multilabel_classifier(df_twitter_train) and returns: ml_predictor