code: def _build_model():
      """Build the model to fit."""
      numeric_transformer = SimpleImputer()
      categorical_transformer = Pipeline(
          steps=[
              ("imputer", SimpleImputer(strategy="most_frequent")),
              ("encoder", OrdinalEncoder()),
          ]
      )
  
      preprocessor = ColumnTransformer(
          transformers=[
              ("num", numeric_transformer, _NUM_FEATURES),
              ("cat", categorical_transformer, _CAT_FEATURES),
          ]
      )
  
      model = Pipeline(
          steps=[
              ("preprocessing", preprocessor),
              (
                  "model",
                  RandomForestClassifier(
                      max_depth=5, n_jobs=-1, random_state=0
                  ),
              ),
          ]
      )
  
      return model
  
file_path: deepchecks/deepchecks/tabular/datasets/classification/adult.py
imports: import typing
  from urllib.request import urlopen
  import joblib
  import pandas
  import sklearn
  from category_encoders import OrdinalEncoder
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from deepchecks.tabular.dataset import Dataset
label_desc: Use image node_id 3 for calling a global function with example usage: _build_model() and returns: model