浮点列表中的最大值索引 | Python

Question

I've looked at quite a few posts but none seem to help.

I want to calcuate Term Frequency & Inverse Document Frequency; a Bag of Words technique used in Deep Learning. The purpose of this code is just to calculate the formula. I do not implement an ANN here.

Below is a minimal code example. It is after the for loop I have this problem.

import math

docs = 1000
words_per_doc = 100  # length of doc
#word_freq = 10
#doc_freq = 100
dp = 4

print('Term Frequency Inverse Document Frequency')
# term, word_freq, doc_freq
words = [['the', 10, 100], ['python', 10, 900]]
tfidf_ = []
for idx, val in enumerate(words):
  print(words[idx][0] + ':')
  word_freq = words[idx][1]
  doc_freq = words[idx][2]

  tf = round(word_freq/words_per_doc, dp)
  idf = round(math.log10(docs/doc_freq), dp)
  tfidf = round((tf*idf), dp)
  print(str(tf) + ' * ' + str(idf) + ' = ' + str(tfidf))
  tfidf_.append(tfidf)
  print()

max_val = max(tfidf)
max_idx = tfidf.index(max_val)

#max_idx = tfidf.index(max(tfidf))
lowest_idx = 1 - max_idx

print('Therefore, \'' + words[max_idx][0] + '\' semantically is more important than  \'' + words[lowest_idx][0] + '\'.')


#print('log(N/|{d∈D:w∈W}|)')

Error:

line 25, in <module>
    max_val = max(tfidf)
TypeError: 'float' object is not iterable

Answer 1

You are trying to pass tfidf on your function instead of tfidf_

tfidf is int and tfidf_ is your list

So code should be

max_val = max(tfidf_)
max_idx = tfidf_.index(max_val)