Usuń 'predict.py'

This commit is contained in:
s152483 2020-04-10 22:18:51 +00:00
parent 17710e4bbb
commit 0c3afb61f9

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@ -1,35 +0,0 @@
import pickle
import sys
import math
import fileinput
model = pickle.load(open("model.pkl", "rb"))
word_index, vocabulary, weights, words_count = model
def predict():
output = []
for line in fileinput.input(openhook=fileinput.hook_encoded("utf-8")):
line = line.rstrip()
fields = line.split('\t')
label = fields[0].strip()
document = fields[0]
terms = document.split(' ')
for term in terms:
if term in words_count:
words_count[term] += 1
else:
words_count[term] = 1
expected = weights[0]
for t in terms:
if t in vocabulary:
expected +=(words_count[t]/len(words_count)*(weights[word_index[t]]))
if expected > 0.9:
output.append(1)
else:
output.append(0)
with open("out.tsv", "w") as out:
for val in output:
out.write(str(val)+"\n")
predict()