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: Next to the current value, the normally distributed new value is set aside 
docstr_tok: ["Next","to","the","current","value",",","the","normally","distributed","new","value","is","set","aside"]
code: def _incremental_change(parameter_name, **kwargs):
      """Next to the current value, the normally distributed new value is set aside"""
      # TODO add the ability to limit the boundaries of the params ranges
      sigma = kwargs["current_value"] * 0.3
      new_value = random.normalvariate(kwargs["current_value"], sigma)
      return {parameter_name: new_value}
  
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 6 for calling the ParametersChanger obj's underlying member method code with example usage: obj._incremental_change(parameter_name) and returns: dict