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Implement Ada boost ensembling, train a boosted decision stump ensemble and Evaluate the effect of boosting
License: MIT License
boosting's Introduction
- Use SFrames to do some feature engineering.
- Modify the decision trees to incorporate weights.
- Implement Adaboost ensembling.
- Use your implementation of Adaboost to train a boosted decision stump ensemble.
- Evaluate the effect of boosting (adding more decision stumps) on performance of the model.
- Explore the robustness of Adaboost to overfitting.
lending-club-data.gl
- decision trees.
- Adaboost ensembling.
- boosted decision stump ensemble.