Deep Learning for Extreme Multi-label Text Classification閱讀筆記
文章目錄 概述 模型 Dynamic max pooling 損失函數 Hidden Bottleneck layer 實驗 參數設置 實驗結果 概述 Extreme multi-label就是說總的標籤量非常多, 成千上萬甚至數百萬. Extreme multi-label text classification主要難點在於數據稀疏, 並且計算量較大(標籤太多). 本文作者對textcnn進行改
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相關文章
- 1. Deep Learning for Extreme Multi-label Text Classification閱讀筆記
- 2. Deep Learning for Extreme Multi-label Text Classification
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