parameters: (cls, sklearn_model)
return_statement: return builder.commit()
docstring: Process a RandomForestClassifier (binary classifier) to convert it into a
             Treelite model
docstring_summary: Process a RandomForestClassifier (binary classifier) to convert it into a
             Treelite model
docstring_tokens: Process a RandomForestClassifier ( binary classifier ) to convert it into a Treelite model
function: def process_model(cls, sklearn_model):
          """Process a RandomForestClassifier (binary classifier) to convert it into a
             Treelite model"""
          builder = treelite.ModelBuilder(
              num_feature=sklearn_model.n_features_, average_tree_output=True,
              threshold_type='float64', leaf_output_type='float64')
          for i in range(sklearn_model.n_estimators):
              # Process i-th tree and add to the builder
              builder.append(cls.process_tree(sklearn_model.estimators_[i].tree_,
                                              sklearn_model))
  
          return builder.commit()
function_tokens: def process_model ( cls , sklearn_model ) : builder = treelite . ModelBuilder ( num_feature = sklearn_model . n_features_ , average_tree_output = True , threshold_type = 'float64' , leaf_output_type = 'float64' ) for i in range ( sklearn_model . n_estimators ) : # Process i-th tree and add to the builder builder . append ( cls . process_tree ( sklearn_model . estimators_ [ i ] . tree_ , sklearn_model ) ) return builder . commit ( )