code: def task_model_builder(model_dir):
      sklearn_model = RandomForestRegressor(
          # n_estimators=100, max_features=int(num_features/3),
          n_estimators=1,
          max_features=int(num_features / 3),
          min_samples_split=5,
          n_jobs=-1,
      )
      return dc.models.SklearnModel(sklearn_model, model_dir)
  
file_path: deepchem/examples/kaggle/KAGGLE_rf_model.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import numpy
  import tempfile
  import shutil
  import deepchem
  from sklearn.ensemble import RandomForestRegressor
  from deepchem.molnet import load_kaggle
label_desc: Use image node_id 1 for calling a global function with example usage: task_model_builder(model_dir) and returns: dc