Stance-Detection-in-Web-and.../CNN
2019-06-16 11:41:05 +05:30
..
conv_net_classes.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
evaluate.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
get_params.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
predictions.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
process4T6SA.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
README.md Updated README 2019-06-16 11:41:05 +05:30
run.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
score.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
T6SA_conv_net_sentence.py Added the CNN Codes 2019-06-16 11:34:28 +05:30
T6SA_process_data.py Added the CNN Codes 2019-06-16 11:34:28 +05:30

Requirements

Python version - 2.7

You need to download Google news vectors 300 dimensional bin file and place it in the main directory to run the code You will need to have Theano=0.7 to run the code. Please refer : https://github.com/nestle1993/SE16-Task6-Stance-Detection

Usage

Training and Testing

 python run.py <Path to the Data Directory>

Printing the scores for each dataset within data directory

 python score.py <Path to the Data Directory>

Printing the tuned hyperparameters for each dataset within data directory

 python get_params.py <Path to the Data Directory>

Note: The Data Directory be one of the preprocessed folders created by the preprocessing script. Example directory structure of the data directory for SemEval Data:

Data_SemE_P
├── Atheism
|   ├── test_clean.txt
|   ├── test_preprocessed.csv
|   ├── train_clean.txt
|   └── train_preprocessed.csv
├── CC
|   ├── test_clean.txt
|   ├── test_preprocessed.csv
|   ├── train_clean.txt
|   └── train_preprocessed.csv
├── FM
|   ├── test_clean.txt
|   ├── test_preprocessed.csv
|   ├── train_clean.txt
|   └── train_preprocessed.csv
├── HC
|   ├── test_clean.txt
|   ├── test_preprocessed.csv
|   ├── train_clean.txt
|   └── train_preprocessed.csv
└── LA
    ├── test_clean.txt
    ├── test_preprocessed.csv
    ├── train_clean.txt
    └── train_preprocessed.csv