class_docstr: Extract model data and port an AdaBoostClassifier classifier.
class_docstr_tok: ["Extract","model","data","and","port","an","AdaBoostClassifier","classifier","."]
docstr: Port a method for a single tree.
  
  Parameters
  ----------
  templates : Dict[str, str]
      All relevant templates.
  language
      The required language.
  converter
      The number converter.
  method_index : str
      The index of a single decision tree.
  class_name : str
      The class name.
  model_data : dict
      The model data of the single decision tree.
  
  Returns
  -------
  out_tree : str
      The created method as string.
docstr_tok: ["Port","a","method","for","a","single","tree",".","Parameters","--","--","--","--","--","templates",":","Dict","[","str",",","str","]","All","relevant","templates",".","language","The","required","language",".","converter","The","number","converter",".","method_index",":","str","The","index","of","a","single","decision","tree",".","class_name",":","str","The","class","name",".","model_data",":","dict","The","model","data","of","the","single","decision","tree",".","Returns","--","--","--","-","out_tree",":","str","The","created","method","as","string","."]
code: def _create_method(
      self,
      templates: Environment,
      language: str,
      converter: Callable[[object], str],
      method_index: str,
      class_name: str,
      model_data: dict,
  ):
      """
      Port a method for a single tree.
  
      Parameters
      ----------
      templates : Dict[str, str]
          All relevant templates.
      language
          The required language.
      converter
          The number converter.
      method_index : str
          The index of a single decision tree.
      class_name : str
          The class name.
      model_data : dict
          The model data of the single decision tree.
  
      Returns
      -------
      out_tree : str
          The created method as string.
      """
      tree = self._create_tree(
          templates,
          language,
          converter,
          model_data.get("lefts"),
          model_data.get("rights"),
          model_data.get("thresholds"),
          model_data.get("classes"),
          model_data.get("indices"),
          0,
          1,
      )
  
      tpl_tree = templates.get_template("combined.tree")
      out_tree = tpl_tree.render(
          tree=tree,
          n_classes=self.meta_info.get("n_classes"),
          n_estimators=self.meta_info.get("n_estimators"),
          method_index=method_index,
          class_name=class_name,
      )
      return out_tree
  
file_path: sklearn-porter/sklearn_porter/estimator/AdaBoostClassifier/__init__.py
imports: from copy import deepcopy
  from json import dumps, encoder
  from textwrap import indent
  from typing import Callable, Tuple, Union
  from jinja2 import Environment
  from loguru import logger
  from sklearn.ensemble.weight_boosting import AdaBoostClassifier
  from sklearn.tree import DecisionTreeClassifier
  from sklearn_porter import enums
  from sklearn_porter import exceptions
  from sklearn_porter.estimator.EstimatorApiABC import EstimatorApiABC
  from sklearn_porter.estimator.EstimatorBase import EstimatorBase
label_desc: Use image node_id 3 for calling the AdaBoostClassifier obj's underlying member method code with example usage: obj._create_method(templates, language, converter, method_index, class_name, model_data) and returns: out_tree