class_docstr: This algorithm combines our ATPE optimizer with Hyperband
class_docstr_tok: ["This","algorithm","combines","our","ATPE","optimizer","with","Hyperband"]
code: def createCanonicalStringFromParameters(
      self, params, hyperparameterSpace
  ):
      newResult = Hyperparameter(
          hyperparameterSpace
      ).convertToFlatValues(params)
      return self.createCanonicalStringFromResult(
          newResult, hyperparameterSpace
      )
  
file_path: hypermax/hypermax/algorithms/adaptive_bayesian_hyperband_optimizer.py
imports: import numpy
  import random
  from math import log, ceil
  from time import time, ctime
  from .optimization_algorithm_base import OptimizationAlgorithmBase
  from .random_search_optimizer import RandomSearchOptimizer
  from pprint import pprint
  from ..hyperparameter import Hyperparameter
  import hyperopt
  import json
  import functools
  import copy
label_desc: Use image node_id 5 for calling the AdaptiveBayesianHyperband obj's underlying member method code with example usage: obj.createCanonicalStringFromParameters(params, hyperparameterSpace) and returns: self