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【paper】A Divide- and-Conquer Approach for Large-scale Multi-label Learning
時間 2021-05-16
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A Divide- and-Conquer Approach for Large-scale Multi-label Learning 添加鏈接描述 一、模型思路 利用特徵向量將訓練數據聚類爲幾個聚類。 通過將每個標籤視爲一個推薦項目(items),將多標籤問題重新表述爲推薦問題(users)。 學習高級分解模型(因子分解機,FM),以向局部集羣的每個點推薦標籤子集。 二、創新點 提出了一種基於分
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