Bag of Tricks for Efficient Text Classification
文章摘要 這篇文章爲文本分類提供了一個簡單又高效的模型，fasttext。這個模型在效果上能比肩複雜的深度學習模型的同時，在速度上又快了幾個量級。fasttext的結構非常簡單，僅僅是word2vec中CBOW模型的一個變形，CBOW是上下文單詞的詞向量平均去預測中心詞，fasttext是整個文檔的單詞的詞向量平均去預測標籤。 文章亮點 這篇個論文的模型非常簡單。熟悉word2vec的同學可能一下
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相關文章
- 1. (36)[EACL] Bag of Tricks for Efficient Text Classification
- 2. Fasttext (Bag of Tricks for Efficient Text Classification) 閱讀筆記
- 3. 論文閱讀：《Bag of Tricks for Efficient Text Classification》
- 4. 【論文筆記】Bag of Tricks for Efficient Text Classification
- 5. Bag of Tricks for Efficient Text Classification(FastText)閱讀筆記
- 6. Bag of Tricks for Image Classification with Convolutional Neural Networks
- 7. Bag of Tricks for Convolutional Neural Networks
- 8. BAG OF TRICKS FOR ADVERSARIAL TRAINING
- 9. 【論文閱讀】Bag of Tricks for Image Classification with Convolutional Neural Networks
- 10. Bag of Tricks for Image Classification with Convolutional Neural Networks論文筆記