DDM（Drift Detection Method）
Introduction 很多機器學習模型都是基於stationary probability distribution（穩定概率分佈）數據樣本的，隨着樣本數據的概率分佈的改變，模型的準確率也會隨之下降，DDM就是這樣一種檢測方法，用於檢測樣本數據的概率分佈的改變。DDM也是作爲concept drift領域一個base line，很多concept drift detector都是以次基礎上作爲
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相關文章
- 1. Concept Drift（概念漂移）
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- 10. 論文閱讀筆記《A Surface Defect Detection Method Based on Positive Samples》