Multi-Label Learning 筆記一A Review on Multi-Label Learning Algorithms
1、定義 定義爲d維的實體空間，爲q個可能標籤的標籤空間。multi-label learning就是從multi-label training set中學習函數 。對於每個multi-label example 是一個d維的特徵向量，就是與相關的一組標籤。對於沒有出現過的實體，多標籤分類器爲x預測出一組合適的標籤。 2、主要挑戰 1、隨着標籤的增加，輸出空間成指數性增長
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