class_docstr: This table's columns are text columns representing JSON data of how
  to extract the train and test datasets, base learner cross-validation method,
  and the stacked ensemble cross-validation method.
  It will contain only a single row.
class_docstr_tok: ["This","table","'s","columns","are","text","columns","representing","JSON","data","of","how","to","extract","the","train","and","test","datasets",",","base","learner","cross-validation","method",",","and","the","stacked","ensemble","cross-validation","method",".","It","will","contain","only","a","single","row","."]
code: def __init__(self):
      self.main_dataset = constants.DEFAULT_EXTRACTION_MAIN_DATASET
      self.test_dataset = constants.DEFAULT_EXTRACTION_TEST_DATASET
      self.meta_feature_generation = (
          constants.DEFAULT_EXTRACTION_META_FEATURE_GENERATION
      )
      self.stacked_ensemble_cv = (
          constants.DEFAULT_EXTRACTION_META_FEATURE_GENERATION
      )
      self.data_statistics = None
  
imports: from __future__ import absolute_import, print_function, division, unicode_literals
  import random
  import string
  from sqlalchemy.ext.declarative import declarative_base
  from sqlalchemy import Column, Text, Integer, Boolean, TypeDecorator, ForeignKey, Table, UniqueConstraint
  from sqlalchemy.orm import relationship
  from sqlalchemy.ext import mutable
  import numpy
  import json
  import os
  from sklearn.model_selection import train_test_split
  from xcessiv import constants
  from xcessiv import exceptions
  from xcessiv import functions
  from xcessiv import app
label_desc: Use image node_id 1 to create a new Extraction object from inherited base classes: Base with example: obj = Extraction()