docstr: Print single measure.
  
  Args:
      measure(str): measure type
      value(list of float): value
code: def print_measure(measure, value):
      """Print single measure.
  
      Args:
          measure(str): measure type
          value(list of float): value
      """
      print(measure + ": {:.2f}%".format(np.mean(value)), end="")
      if not np.isscalar(value):
          print(" (+/- {:.2f}%)".format(np.std(value)), end="")
      print()
  
imports: import csv
  import pickle
  import numpy
  import tensorflow
  from os import PathLike
  from pathlib import Path
  from nlp_architect.models.absa.utils import _read_generic_lex_for_similarity
  from nlp_architect.models.absa import TRAIN_OUT, TRAIN_LEXICONS, GENERIC_OP_LEX, LEXICONS_OUT
  from scipy.spatial.distance import cosine
  from sklearn.model_selection import StratifiedKFold
  from tensorflow.keras.layers import Dense, Dropout
  from tensorflow.keras.models import Sequential, load_model
  from nlp_architect.utils.embedding import load_word_embeddings
label_desc: Use image node_id 19 for calling the RerankTerms obj's underlying member method code with example usage: obj.print_measure(measure, value) without return types