classifier_hyperopt_tuning.py 文件源码

def function(params):
  """
  Function to be optimized.
  """
  # generate config
  config = jubatus_config(params)
  # create a classifier service.
  classifier = Classifier.run(config)
  # scoring metric (default accuracy metric)
  metric = accuracy_score
  # calculate cross-validation score
  score = cv_score(classifier, dataset, metric=metric)
  # stop the classifier
  classifier.stop()
  # print score and hyperparameters
  print_log(score, params)
  # hyperopt only minimize target function and we convert the accuracy score to be minimized.
  return -1.0 * score