[ML 스터디] Chapter6. Ensemble Learning

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카테고리:

Main Reference:
- 고려대학교 산업경영공학부 DSBA 연구실 - 강필성 교수님

중간에 등장하는 ppt는 강의자료를 캡처한 것입니다.


🚌 Ensemble Learning

  • No Free Lunch Theorem
  • Bias-Variance Decomposition
  • Bagging
  • Random Forest
  • Boosting
  • Stacking


🚌 Lecture Note

No Free Lunch Theorem

ML_Week6-02 ML_Week6-03 ML_Week6-04 ML_Week6-05 ML_Week6-06


Bias-Variance Decomposition

ML_Week6-07 ML_Week6-08 ML_Week6-09 ML_Week6-10 ML_Week6-11 ML_Week6-12 ML_Week6-13 ML_Week6-14


Bagging

ML_Week6-15 ML_Week6-16 ML_Week6-17 ML_Week6-18 ML_Week6-19


Random Forest

ML_Week6-20 ML_Week6-21 ML_Week6-22 ML_Week6-23


Ada Boosting

ML_Week6-24 ML_Week6-25 ML_Week6-26 ML_Week6-27


Gradient Boosting

ML_Week6-28 ML_Week6-29 ML_Week6-30 ML_Week6-31 ML_Week6-32


Stacking

ML_Week6-33



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