Machine Learning 1: UNIT 4 (B) PPTs: Ensemble Learning and Random Forests PPTs

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  UNIT 4 (B)

Ensemble Learning and Random Forests

1.     Voting Classifiers

2.     Bagging and pasting

3.     Bagging and Pasting in Scikit-Learn

4.     Out-of-Bag Evaluation

5.     Random Patches and Random Subspaces

6.     Random Forests

7.     Extra-Trees

8.     Feature Importance

9.     Boosting

10.  AdaBoost

11.  Gradient Boosting

12.  Stacking



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