基于深度神经网络的文本分类 基于主流的lstm模型
原始数据和中间训练 模型链接：https://pan.baidu.com/s/1jge-RGWc_YXvnOKxEr0pkg 提取码：u5iq 复制此内容后，打开百度网盘手机App，操作更方便
# -*- 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