code: def get_param_baseline():
      default_params = {
          "C": 1,
          "vectorizer_dict_size": 75000,  # size of TFIDF vectorizer dictionary; used only in text model
          "proc.ngram_range": (
              1,
              5,
          ),  # range of n-grams for TFIDF vectorizer dictionary; used only in text model
          "proc.skew_threshold": 0.99,  # numerical features whose absolute skewness is greater than this receive special power-transform preprocessing. Choose big value to avoid using power-transforms
          "proc.impute_strategy": "median",  # strategy argument of sklearn.SimpleImputer() used to impute missing numeric values
          "penalty": "L2",  # regularization to use with regression models
          "handle_text": IGNORE,  # how text should be handled: `ignore` - don't use NLP features; `only` - only use NLP features; `include` - use both regular and NLP features
      }
      return default_params
  
imports: import logging
  from autogluon.core.constants import BINARY
label_desc: Use image node_id 1 for calling a global function with example usage: get_param_baseline() and returns: default_params