code: def _build_model():
      """Build the model to fit."""
      return Pipeline(
          steps=[
              (
                  "preprocessing",
                  ColumnTransformer(
                      transformers=[
                          ("num", SimpleImputer(), _NUM_FEATURES),
                          (
                              "cat",
                              Pipeline(
                                  steps=[
                                      (
                                          "imputer",
                                          SimpleImputer(
                                              strategy="most_frequent"
                                          ),
                                      ),
                                      ("encoder", OneHotEncoder()),
                                  ]
                              ),
                              _CAT_FEATURES,
                          ),
                      ]
                  ),
              ),
              (
                  "model",
                  RandomForestClassifier(
                      criterion="entropy",
                      n_estimators=40,
                      random_state=0,
                  ),
              ),
          ]
      )
  
file_path: deepchecks/deepchecks/tabular/datasets/classification/phishing.py
imports: import typing
  from urllib.request import urlopen
  import joblib
  import pandas
  import sklearn
  from category_encoders import OneHotEncoder
  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 4 for calling a global function with example usage: _build_model() and returns: Pipeline