class_docstr: Class for the hyperparameters changing in the operation
  
  :param operation_name: name of operation to get hyperparameters for
  :param current_params: current parameters value
class_docstr_tok: ["Class","for","the","hyperparameters","changing","in","the","operation",":","param","operation_name",":","name","of","operation","to","get","hyperparameters","for",":","param","current_params",":","current","parameters","value"]
docstr: Change values of hyperparameters by different ways
  
  :param params_list: list with hyperparameters names
docstr_tok: ["Change","values","of","hyperparameters","by","different","ways",":","param","params_list",":","list","with","hyperparameters","names"]
code: def new_params_dict(self, params_list):
      """Change values of hyperparameters by different ways
  
      :param params_list: list with hyperparameters names
      """
  
      _change_by_name = {
          "lagged": {"window_size": self._incremental_change},
          "sparse_lagged": {"window_size": self._incremental_change},
      }
  
      params_dict = {}
      for parameter_name in params_list:
          # Get current value of the parameter
          current_value = self._get_current_parameter_value(
              parameter_name
          )
  
          # Perform parameter value change using appropriate function
  
          operation_dict = _change_by_name.get(self.operation_name)
          if operation_dict is not None:
              func = operation_dict.get(parameter_name)
          else:
              # Default changes perform with random choice
              func = self._random_change
          if func is None:
              func = self._random_change
          parameters = {
              "operation_name": self.operation_name,
              "current_value": current_value,
          }
  
          param_value = func(parameter_name, **parameters)
          params_dict.update(param_value)
  
      return params_dict
  
file_path: FEDOT/fedot/core/pipelines/tuning/hyperparams.py
imports: import random
  import numpy
  from golem.core.log import default_log
  from golem.core.tuning.hyperopt_tuner import get_parameter_hyperopt_space
  from hyperopt.pyll.stochastic import sample
  from fedot.core.pipelines.tuning.search_space import PipelineSearchSpace
label_desc: Use image node_id 3 for calling the ParametersChanger obj's underlying member method code with example usage: obj.new_params_dict(params_list) and returns: params_dict