39 lines
1.5 KiB
Python
39 lines
1.5 KiB
Python
from collections import defaultdict
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import math
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import pickle
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open_file = open('naive_base_model.pkl', 'rb')
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pickle_loaded = pickle.load(open_file)
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paranomal_class_logprob, skeptic_class_logprob, word_logprobs = pickle_loaded
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#pickle_loaded=pickle.load(open_file)
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#paranomal_class_logprob, skeptic_class_logprob, word_logprobs = pickle_loaded
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#Niektórych słów nie bezie w zbiorze treningowym dev-0 i dev-A
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def prediction(input,output):
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output_file = open(output,'w')
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with open(input,encoding='utf-8') as in_file:
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for line in in_file:
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temp_paranormal_logprob = paranomal_class_logprob
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temp_skeptic_logprob = skeptic_class_logprob
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text, timestamp = line.rstrip('\n').split('\t')
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tokens = text.lower().split(' ')
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for token in tokens:
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if token not in word_logprobs['paranormal']:
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word_logprobs['paranormal'][token] = 0
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if token not in word_logprobs['skeptic']:
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word_logprobs['skeptic'][token] = 0
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temp_paranormal_logprob += paranomal_class_logprob + word_logprobs['paranormal'][token]
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temp_skeptic_logprob += skeptic_class_logprob + word_logprobs['skeptic'][token]
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if temp_paranormal_logprob > temp_skeptic_logprob:
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output_file.write('0\n')
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else:
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output_file.write('1\n')
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def main():
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prediction('dev-0/in.tsv','dev-0/out.tsv')
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prediction('test-A/in.tsv/in.tsv','test-A/out.tsv')
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main()
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