parameters: (self, field)
return_statement: return super(_Classifier, self)._get(field)
docstring: Get the value of a given field. The following table describes each
          of the fields below.
  
          +-------------------------+--------------------------------------------------------------------------------+
          | Field                   | Description                                                                    |
          +=========================+================================================================================+
          | column_subsample        | Percentage of the columns for training each individual tree                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | features                | Names of the feature columns                                                   |
          +-------------------------+--------------------------------------------------------------------------------+
          | max_depth               | The maximum depth of the individual decision trees                             |
          +-------------------------+--------------------------------------------------------------------------------+
          | max_iterations          | Maximum number of iterations for training (one tree is trained per iteration)  |
          +-------------------------+--------------------------------------------------------------------------------+
          | min_child_weight        | Minimum weight assigned to leaf nodes                                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | min_loss_reduction      | Minimum loss reduction required for splitting a node                           |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_features            | Number of feature columns in the model                                         |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_unpacked_features   | Number of features in the model (including unpacked dict/list type columns)    |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_examples            | Number of training examples                                                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_validation_examples | Number of validation examples                                                  |
          +-------------------------+--------------------------------------------------------------------------------+
          | row_subsample           | Percentage of the rows sampled for training each individual tree               |
          +-------------------------+--------------------------------------------------------------------------------+
          | step_size               | Step_size used for combining the weight of individual trees                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | target                  | Name of the target column                                                      |
          +-------------------------+--------------------------------------------------------------------------------+
          | training_accuracy       | Classification accuracy measured on the training data                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | training_time           | Time spent on training the model in seconds                                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | trees_json              | Tree encoded using JSON                                                        |
          +-------------------------+--------------------------------------------------------------------------------+
          | validation_accuracy     | Classification accuracy measured on the validation set                         |
          +-------------------------+--------------------------------------------------------------------------------+
          | unpacked_features       | Feature names (including expanded list/dict features)                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | random_seed             | Seed for row and column subselection                                           |
          +-------------------------+--------------------------------------------------------------------------------+
          | metric                  | Performance metric(s) that are tracked during training                         |
          +-------------------------+--------------------------------------------------------------------------------+
  
  
          Parameters
          ----------
          field : string
              Name of the field to be retrieved.
  
          Returns
          -------
          out : [various]
              The current value of the requested field.
docstring_summary: Get the value of a given field. The following table describes each
          of the fields below.
docstring_tokens: Get the value of a given field . The following table describes each of the fields below .
function: def _get(self, field):
          """
          Get the value of a given field. The following table describes each
          of the fields below.
  
          +-------------------------+--------------------------------------------------------------------------------+
          | Field                   | Description                                                                    |
          +=========================+================================================================================+
          | column_subsample        | Percentage of the columns for training each individual tree                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | features                | Names of the feature columns                                                   |
          +-------------------------+--------------------------------------------------------------------------------+
          | max_depth               | The maximum depth of the individual decision trees                             |
          +-------------------------+--------------------------------------------------------------------------------+
          | max_iterations          | Maximum number of iterations for training (one tree is trained per iteration)  |
          +-------------------------+--------------------------------------------------------------------------------+
          | min_child_weight        | Minimum weight assigned to leaf nodes                                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | min_loss_reduction      | Minimum loss reduction required for splitting a node                           |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_features            | Number of feature columns in the model                                         |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_unpacked_features   | Number of features in the model (including unpacked dict/list type columns)    |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_examples            | Number of training examples                                                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | num_validation_examples | Number of validation examples                                                  |
          +-------------------------+--------------------------------------------------------------------------------+
          | row_subsample           | Percentage of the rows sampled for training each individual tree               |
          +-------------------------+--------------------------------------------------------------------------------+
          | step_size               | Step_size used for combining the weight of individual trees                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | target                  | Name of the target column                                                      |
          +-------------------------+--------------------------------------------------------------------------------+
          | training_accuracy       | Classification accuracy measured on the training data                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | training_time           | Time spent on training the model in seconds                                    |
          +-------------------------+--------------------------------------------------------------------------------+
          | trees_json              | Tree encoded using JSON                                                        |
          +-------------------------+--------------------------------------------------------------------------------+
          | validation_accuracy     | Classification accuracy measured on the validation set                         |
          +-------------------------+--------------------------------------------------------------------------------+
          | unpacked_features       | Feature names (including expanded list/dict features)                          |
          +-------------------------+--------------------------------------------------------------------------------+
          | random_seed             | Seed for row and column subselection                                           |
          +-------------------------+--------------------------------------------------------------------------------+
          | metric                  | Performance metric(s) that are tracked during training                         |
          +-------------------------+--------------------------------------------------------------------------------+
  
  
          Parameters
          ----------
          field : string
              Name of the field to be retrieved.
  
          Returns
          -------
          out : [various]
              The current value of the requested field.
          """
          return super(_Classifier, self)._get(field)
function_tokens: def _get ( self , field ) : return super ( _Classifier , self ) . _get ( field )