mirror of https://github.com/explosion/spaCy.git
Merge branch 'master' of ssh://github.com/explosion/spaCy
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21386aa68a
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@ -78,7 +78,7 @@ p A simple work-around is to average the vectors of several words, and use that
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+code.
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+code.
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>>> say_verbs = ['pleaded', 'confessed', 'remonstrated', 'begged', 'bragged', 'confided', 'requested']
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>>> say_verbs = ['pleaded', 'confessed', 'remonstrated', 'begged', 'bragged', 'confided', 'requested']
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>>> say_vector = sum(nlp.vocab[verb].vector for verb in say_verbs) / len(say_verbs)
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>>> say_vector = sum(nlp.vocab[verb].vector for verb in say_verbs) / len(say_verbs)
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>>> words.sort(key=lambda w: cosine(w.vector * say_vector))
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>>> words.sort(key=lambda w: cosine(w.vector, say_vector))
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>>> words.reverse()
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>>> words.reverse()
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>>> print('1-20', ', '.join(w.orth_ for w in words[0:20]))
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>>> print('1-20', ', '.join(w.orth_ for w in words[0:20]))
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1-20 bragged, remonstrated, enquired, demurred, sighed, mused, intimated, retorted, entreated, motioned, ranted, confided, countersued, gestured, implored, interceded, muttered, marvelled, bickered, despaired
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1-20 bragged, remonstrated, enquired, demurred, sighed, mused, intimated, retorted, entreated, motioned, ranted, confided, countersued, gestured, implored, interceded, muttered, marvelled, bickered, despaired
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