code: def model_builder(model_dir):
      sklearn_model = RandomForestClassifier(
          class_weight="balanced", n_estimators=500, n_jobs=-1
      )
      return dc.models.SklearnModel(sklearn_model, model_dir)
  
file_path: deepchem/examples/sweetlead/sweet.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import sys
  import numpy
  import pandas
  import deepchem
  from sklearn.ensemble import RandomForestClassifier
  from deepchem.models.multitask import SingletaskToMultitask
  from deepchem import metrics
  from deepchem.metrics import Metric
  from deepchem.models.sklearn_models import SklearnModel
label_desc: Use image node_id 1 for calling a global function with example usage: model_builder(model_dir) and returns: dc