毕业设计 word2vec 加lstm 文本分类

基于深度神经网路的文本分类 基于主流的lstm模型 

原始的数据和中间的训练 模型 链接：https://pan.baidu.com/s/1jge-RGWc_YXvnOKxEr0pkg 
提取码：u5iq 
复制这段内容后打开百度网盘手机App，操作更方便哦

# -*- coding: utf-8 -*-
import pandas as pd
import gensim
import jieba
import re
import numpy as np

from sklearn.model_selection import train_test_split
from gensim.models import KeyedVectors
from gensim.scripts.glove2word2vec import glove2word2vec
import pandas as pd
import numpy as np 
import torch
from torch import nn
import torch.utils.data as data
import torch.nn.functional as F
from torch import tensor
from sklearn.metrics import f1_score
from datetime import datetime 
import time 

from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM,GRU
from keras import optimizers
import keras

# 读取数据 
data=pd.read_csv('comments.txt',encoding='utf-8',sep=' ',delimiter="\t")
data.values
print(len(data.values