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Data Science/ML & DL

8. Ensemble Methods and Boosting

eatplaylove 2024. 4. 15. 20:28

https://eglife.tistory.com/55

 

7. Decision Trees

https://eglife.tistory.com/54 6. Overfitting & Regularization https://eglife.tistory.com/48 5. Classification 2 (Bayes Classifiers) https://eglife.tistory.com/47 4. Classification 1 (Logistic Regression) https://eglife.tistory.com/46 3. Linear Regression 2

eglife.tistory.com

ch9.pdf
15.14MB

 

 

지난 시간 배웠던 의사결정나무를 Upgrade 해줄 수 있는 방법이다.

 

있는 Data를 좀 더 효율적으로 쓰기 위한 앙상블기법 여러 개를 공부해보자.

 

Bootstrap 기법
Baaging 등장
Bagging = Best : error 1/B, Worst : error 1배
Bagging + Decision Tree, Randomforest, Boosting

 

Adaboost
Adaboost - min(exponential error) = Stagewise select

 

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