GitHub / akash18tripathi / MAGNET-Multi-Label-Text-Classi-cation-using-Attention-based-Graph-Neural-Network
This GitHub repository provides an implementation of the paper "MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network" . MAGNET is a state-of-the-art approach for multi-label text classification, leveraging the power of graph neural networks (GNNs) and attention mechanisms.
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Language: Jupyter Notebook
Size: 3.98 MB
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Created at: almost 2 years ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago
Topics: adjacency-matrix, attention-mechanism, bert, bert-embeddings, bilstm, binary-relevance, classifier-chains, cnn, embeddings, glove-embeddings, graph-neural-networks, hierarchical-models, multilabel-classification, onevsrestclassifier, reuters-dataset, text-classification, text-preprocessing-techniques, toxic-comment-classification