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prats226 / semantic_transfer_learning.py
Created January 31, 2017 10:01
Sentiment classification using transfer learning
import collections, math, random, numpy
import tensorflow as tf
from sklearn.cross_validation import train_test_split
sentences = """hated the movie it was stupid;\ni hated it so boring;\nawesome the movie was inspiring;\nhated it what a disaster;\nwe hated the movie they were idiotic;\nhe was stupid, hated her;\nstupid movie is boring;\ninspiring ourselves, awesome;\ninspiring me, brilliant;\nwe hated it they were rubbish;\nany inspiring movie is amazing;\nit was stupid what a disaster;\nits stupid, rubbish;\nstupid, idiotic!;\nawesome great movie;\nboring, must be hated;\nhe was boring the movie was stupid;\nboring movie was a disaster;\nboth boring and rubbish;\nso boring and idiotic;\ngreat to amazing;\ndisaster, more than hated;\nbetween disaster and stupid;\ndisaster, so boring;\nawesome movie, brilliant;\ntoo awesome she was amazing;\nhe was brilliant loved it;\ndisaster, only idiotic;\nrubbish movie hated him;\nit was rubbish, why so stupid?;\nrubbish, too boring;\nrubbish, disaster!;\nrubbish, very