文件列表:

batchgen.py (3805, 2018-02-25)
cnn.py (3923, 2018-02-25)
cnn_lstm.py (3845, 2018-02-25)
lstm.py (2509, 2018-02-25)
lstm_cnn.py (4133, 2018-02-25)
requirements.txt (24, 2018-02-25)
train.py (9303, 2018-02-25)

# CS291K Sentiment Analysis of Twitter data using a combined CNN-LSTM Neural Network model - Paper: https://www.academia.edu/35947062/Twitter_Sentiment_Analysis_using_combined_LSTM-CNN_Models - Blog Post: http://konukoii.com/blog/2018/02/19/twitter-sentiment-analysis-using-combined-lstm-cnn-models/ ### Motivation This project seeks to extend the work we did previously on sentiment analysis using simple Feed-Foward Neural Networks (Found here: [paper](https://www.academia.edu/304***927/Twitter_Sentiment_Analysis_with_Neural_Networks) & [repo](https://github.com/pmsosa/Twitter-Sentiment-Analysis)). Instead, we wish to experiment with building a combined CNN-LSTM Neural Net model using Tensorflow to perform sentiment analysis on Twitter data. ### Dependencies ``` sudo -H pip install -r requirements.txt ``` ### Run the Code - On train.py change the variable MODEL_TO_RUN = {0 or 1} - 0 = CNN-LSTM - 1 = LSTM-CNN - Feel free to change other variables (batch_size, filter_size, etc...) - Run ```python train.py``` (or, with proper permissions, ```./train.py``` ### Code Structure ### - [lstm_cnn.py](./lstm_cnn.py) : Contains the LSTM_CNN Model class to be instantiated. - [cnn_lstm.py](./cnn_lstm.py) : Contains the CNN_LSTM Model class to be instantiated. - [train.py](./train.py) : Main runner for the code. It instantiates a model, trains it and validates it. - [batchgen.py](./batchgen.py) : Contains a couple of functions needed to pre-process and tokenize the dataset.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：