5、ML-kNN A lazy learning approach to multi-label learning
論文相關內容 本文中解決多標記問題的方法： 本文提出了一種基於k近鄰算法的多標籤懶惰學習方法——ML-KNN。具體來說，對於每個不可見的實例，首先確定其在訓練集中的K個近鄰。然後，根據從這些相鄰實例的標籤集中獲得的統計信息，即每個可能類的相鄰實例的數量，利用極大後驗(maximum a posteriori, MAP)原則來確定不可見實例的標籤集。 ML-KNN 看了周志華老師的多標籤綜述中此算法
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相關文章
- 1. A holistic approach to semi-supervised learning
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