class_docstr: RANdom SAmple Consensus (RANSAC) algorithm with DecisionTreeRegressor as core
  Task type - regression
code: def __init__(self, params: Optional[OperationParameters]):
      super().__init__(params)
      self.inner_model = DecisionTreeRegressor()
  
      # TODO valer1435 | Delete this after removing compatibility with sklearn<1.1
      if parse_version(sklearn.__version__) < parse_version("1.1.0"):
          self.operation = RANSACRegressor(
              base_estimator=self.inner_model, **self.params.to_dict()
          )
      else:
          self.operation = RANSACRegressor(
              estimator=self.inner_model, **self.params.to_dict()
          )
  
imports: from copy import copy
  from typing import Optional
  import numpy
  import sklearn
  from golem.core.log import default_log
  from pkg_resources import parse_version
  from sklearn.ensemble import IsolationForest
  from sklearn.linear_model import LinearRegression, RANSACRegressor
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.tree import DecisionTreeRegressor
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
label_desc: Use image node_id 1 to create a new NonLinearRegRANSACImplementation object from inherited base classes: RegRANSACImplementation with example: obj = NonLinearRegRANSACImplementation(params)