6회차 (2/21)

1. Ensemble Learning
   • Bagging
   • Random Forest
   • Boosting
   • AdaBoost
   • XGBoost
2. 예습 아래 동영상 꼼꼼히 보고 와주세요! (총 10분!)

• Ensemble learners https://www.youtube.com/watch?v=Un9zObFjBH0&t=1s

• Bootstrap aggregating bagging https://www.youtube.com/watch?v=2Mg8QD0F1dQ

• Boosting : Ada Boost https://www.youtube.com/watch?v=GM3CDQfQ4sw

• Random Forest, Rotation Forest(포스트) https://ratsgo.github.io/machine%20learning/2017/03/17/treeensemble/

• XGBOOST https://brunch.co.kr/@snobberys/137

1. 과제 ensemble learning
   (~2/28) 7회차 스터디 때까지>

2. 복습 , 내용복습하기

REF

• Ensemble learners https://www.youtube.com/watch?v=Un9zObFjBH0&t=1s
• Bootstrap aggregating bagging https://www.youtube.com/watch?v=2Mg8QD0F1dQ
• Boosting : Ada Boost https://www.youtube.com/watch?v=GM3CDQfQ4sw
• Random Forest, Rotation Forest(포스트) https://ratsgo.github.io/machine%20learning/2017/03/17/treeensemble/

• XGBOOST,,, 수식최고 https://brunch.co.kr/@snobberys/137

• 위의자료 +a 의 ppt

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