1. 概念漂移(concept drift)
背景：概念漂移指的是數據流中的潛在數據分布隨時間發生不可預測的變化，使原有的分類器分類不准確或決策系統無法正確決策，常見於推薦系統、金融領域、決策等
Concept drift refers to unforeseeable changes in the underlying data distribution of data streams over time.
定義：Concept drift in machine learning and data mining refers to the change in the relationships between input and output data in the underlying problem over time. (https://machinelearningmastery.com/gentle-introduction-concept-drift-machine-learning/)
我的理解：目標函數target隨時間發生不可預測性變化。比如：input(x1) --> target(x1) 概念漂移: input(x1) --> target(x2).
2. 概念漂移檢測(concept drift detection method)
待整理。