Sentiment Classifier based on traditional Maching learning methods, eg. Bayes, SVM ,DecisionTree, KNN and Deeplearning method like MLP, CNN, RNN(LSTM).
All code in this project is implemented in Python3.6+.
And all the essential packages are listed in requirements.txt, you can install them by
pip install -r requirements.txt -i https://pypi.douban.com/simple/
Anaconda or virtualenv + virtualenvwrapper are strongly recommended to manage your Python environments.
1、语料
电影评论，训练集合20000（正向10000，负向10000）
电影评论，测试集合20000（正向3000，负向3000）
2、语料处理
使用jieba进行分词
3、输入向量化
使用预先训练的wordvector.bin文件进行向量化
对于传统机器学习算法，要求输入的是N维向量， 采用句子向量求和平均
对于CNN，RNN深度学习算法，要求输入的是N*M维向量，分别对应查找并生成向量
| Algorithm | Accuracy |
|---|---|
| DecisionTree | 0.6907302434144715 |
| Bayes | 0.7437479159719906 |
| KNN | (n=14)0.7909303101033678 |
| SVM | 0.8302767589196399 |
| MLP | (20epoches) 0.8359 |
| CNN | (20epoches) 0.8376 |
| LSTM | (20epoches) 0.8505 |