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DTEL1 - 8 Sklearn Trees
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Classroom Contents
Decision Trees and Ensemble Methods
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- 1 DTEL1 - 1 Welcome to DTE class
- 2 DTEL1 - 2 Class Introduction
- 3 DTEL1 - 3 Introduction to Decision Trees
- 4 DTEL1 - 4 Impurity Functions
- 5 DTEL1 - 5 CART Algorithm
- 6 DTEL1 - 6 Basic Properties of Decision Trees
- 7 DTEL1 7 Basic Regularization of Trees
- 8 DTEL1 - 8 Sklearn Trees
- 9 DTEL1 - 9 Conclusion
- 10 DTEL2 2 1 Introduction
- 11 DTEL2 2 2 Bias variance trade off
- 12 DTEL2 2 3 Bias variance Decomposition
- 13 DTEL2 2 4 Generalizations of bias variance tradeoff
- 14 DTEL2 2 5 ExtraTrees Algorithm
- 15 DTEL2 2 6 ExtraTrees with Sklearn
- 16 DTEL2 2 7 Conclusion
- 17 DTEL3 3 1 Introduction
- 18 DTEL3 3 2 Bootstrap
- 19 DTEL3 3 3 Bagging
- 20 DTEL3 3 4 1 Example
- 21 DTEL3 3 5 Random Forest
- 22 DTEL3 3 4 2 Example Notebook
- 23 DTEL3 3 6 General Ensembling
- 24 DTEL4 4 1 Introduction
- 25 DTEL4 4 2 Proximities
- 26 DTEL4 4 3 Proximities Visualizations
- 27 DTEL4 4 4 Feature Importance's
- 28 DTEL4 4 5 Limitations of Tree Feature Importance
- 29 DTEL4 4 6 Feature Importance's in Random Forest
- 30 DTEL4 4 7 Summary
- 31 DTEL5 5 1 Introduction
- 32 DTEL5 5 2 Boosting
- 33 DTEL5 5 3 Gradient Boosting
- 34 DTEL5 5 4 XGBoost
- 35 DTEL5 5 5 LightGBM
- 36 DTEL5 5 6 CatBoost
