code: def _determine_unk_polarities(terms, polarities, neg, pos):
      for i, term in enumerate(terms):
          if np.average(pos[i]) <= np.average(neg[i]):
              polarities[term] = "POS"
          else:
              polarities[term] = "NEG"
  
      return polarities
  
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 10 for calling the RerankTerms obj's underlying member method code with example usage: obj._determine_unk_polarities(terms, polarities, neg, pos) and returns: polarities