berksudan/GCN-Text-Classification
Text Classification using Graph Convolutional Neural Networks and Natural Language Processing Techniques
This project helps quickly categorize large collections of text documents, such as news articles, movie reviews, or scientific abstracts, into predefined topics or labels. You input a dataset of text documents, and it outputs a trained model that can classify new documents, along with performance metrics like accuracy, precision, and recall. This is ideal for data scientists or researchers who need to automatically organize and understand document corpora.
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Use this if you need to classify documents into distinct categories and are interested in exploring deep learning methods like Graph Convolutional Networks for improved accuracy.
Not ideal if you primarily work on Windows or Mac, as it's designed for Linux, or if you require a simple, out-of-the-box solution without command-line execution and environment setup.
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25
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4
Language
Python
License
MIT
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Last pushed
Feb 04, 2025
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