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使用张量流来理解LSTM模型以进行情绪分析

我正在尝试使用Tensorflow学习用于情绪分析的LSTM模型,我已经完成了LSTM模型.

下面的代码(create_sentiment_featuresets.py)生成5000个正面句子和5000个否定句子的词典.

import nltk
from nltk.tokenize import word_tokenize
import numpy as np
import random
from collections import Counter
from nltk.stem import WordNetLemmatizer

lemmatizer = WordNetLemmatizer()

def create_lexicon(pos, neg):
    lexicon = []
    with open(pos, 'r') as f:
        contents = f.readlines()
        for l in contents[:len(contents)]:
            l= l.decode('utf-8')
            all_words = word_tokenize(l)
            lexicon += list(all_words)
    f.close()

    with open(neg, 'r') as f:
        contents = f.readlines()    
        for l in contents[:len(contents)]:
            l= l.decode('utf-8')
            all_words = word_tokenize(l)
            lexicon += list(all_words)
    f.close()

    lexicon …
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python machine-learning deep-learning lstm tensorflow

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