Tutorial 02 - clairedavid/ml_in_hep GitHub Wiki
Questions
Valid samples never used.
Proba: is the reasoning done legit? It gets the proba only in the last leaf ...
Scikit: ?
Should be BDTs
Use thee GridSearch example: https://colab.research.google.com/github/ageron/handson-ml2/blob/master/06_decision_trees.ipynb
Using Harrison's dataset
- Intro
- The manual decision stump
- Decision Tree
- Random Forest
- Make a ROC curve : compare performance
- AdaBoost
- Add to ROC curve
- Bonus: XGBoost (?)
When to add the validation - overlay - training curves?
Seaborn? That would be good for them. Or assignment? Feature importance!
Gradient Boosting in Python/Scikit-Learn
Excellent source https://towardsdatascience.com/gradient-boosting-classification-explained-through-python-60cc980eeb3d