docstr: Print evaluation results.
  
  Args:
      precision(list of float): precision
      recall(list of float): recall
      f1(list of float): f measure
code: def print_evaluation_results(self, precision, recall, f1):
      """Print evaluation results.
  
      Args:
          precision(list of float): precision
          recall(list of float): recall
          f1(list of float): f measure
      """
      print()
      self.print_measure("Precision", precision)
      self.print_measure("Recall", recall)
      self.print_measure("F-measure", f1)
      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 18 for calling the RerankTerms obj's underlying member method code with example usage: obj.print_evaluation_results(precision, recall, f1) without return types