CorNet Correlation Networks for Extreme Multi-label Text Classification

Related tags

Text Data & NLPCorNet
Overview

CorNet

Correlation Networks for Extreme Multi-label Text Classification

Prerequisites

  • python==3.6.3
  • pytorch==1.2.0
  • torchgpipe==0.0.5
  • click==7.0
  • ruamel.yaml==0.16.5
  • numpy==1.16.2
  • scipy==1.2.1
  • scikit-learn==0.20.3
  • gensim==3.7.2
  • nltk==3.2.4
  • tqdm==4.31.1
  • joblib==0.13.2
  • logzero==1.5.0

Datasets

Pretrained Word Embeddings in gensim format

Run

Preprocess (the EUR-Lex dataset is already tokenized in advance)

./scripts/preprocess_eurlex.sh

or (the other datasets need to be tokenized using NLTK)

./scripts/preprocess_others.sh

Train and evaluate

./scripts/run_models.sh

Baselines

The codes for the baseline models are adapted from the following repositories: XML-CNN, BERT, MeSHProbeNet, and AttentionXML.

Owner
Guangxu Xun
Guangxu Xun
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