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run.py
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run.py
@ -63,10 +63,10 @@ model_len = len(model)
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for index, words_1_3 in enumerate(model):
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if index % 100000 == 0:
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print(f'normalizacja: {index / model_len}')
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occurences = sum(model[words_1_3].values())
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occurrences = sum(model[words_1_3].values())
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for word_2 in model[words_1_3]:
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model[words_1_3][word_2] += alpha
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model[words_1_3][word_2] /= float(occurences + alpha + len(word_2))
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model[words_1_3][word_2] /= float(occurrences + alpha + len(word_2))
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make_prediction('test-A')
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