PyTorch 1.6 and Python 3.7 implementation of Graph Convolutional Networks for Text Classification [1].
Tested on the 20NG/R8/R52/Ohsumed/MR data set, the code on this repository can achieve the effect of the paper.
dataset | 20NG | R8 | R52 | Ohsumed | MR |
---|---|---|---|---|---|
TextGCN(official) | 0.8634 | 0.9707 | 0.9356 | 0.6836 | 0.7674 |
This repo. | 0.8618 | 0.9704 | 0.9354 | 0.6827 | 0.7643 |
NOTE: The result of the experiment is to repeat the run 10 times, and then take the average of accuracy.
data_processor.py
(Already done)build_graph.py
(Already done)trainer.py
[1] Yao, L. , Mao, C. , & Luo, Y. . (2018). Graph convolutional networks for text classification.