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Machine learning
Random Forest와 Extra TreesRandom Forest and Extra Trees
Bagging 뒤에도 남는 Tree 간 오류 상관을 Random Forest(Feature 무작위화)와 Extra Trees(Threshold 무작위화)가 각각 어떻게 다루는지 비교한다.The tree-to-tree error correlation that bagging leaves behind, and how Random Forest (random features) and Extra Trees (random thresholds) tackle it.
Decision Tree, Bagging과 OOBDecision Tree, Bagging and OOB
Decision Tree가 흔들리는 이유, Bagging이 Bootstrap과 Aggregation으로 그 흔들림을 안정성으로 바꾸는 방식, OOB가 실제로 추정하는 것.Why decision trees are unstable, how bagging turns that instability into stability with bootstrap and aggregation, and what OOB really estimates.