code: def model_builder(model_dir):
      sklearn_model = RandomForestRegressor(n_estimators=500)
      return SklearnModel(sklearn_model, model_dir)
  
file_path: deepchem/examples/nci/nci_rf.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import numpy
  import shutil
  from deepchem.molnet import load_nci
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestRegressor
  from deepchem.data import Dataset
  from deepchem.models.multitask import SingletaskToMultitask
  from deepchem import metrics
  from deepchem.metrics import Metric
  from deepchem.models.sklearn_models import SklearnModel
  from deepchem.utils.evaluate import Evaluator
label_desc: Use image node_id 1 for calling a global function with example usage: model_builder(model_dir) and returns: SklearnModel