Chapter 12: Advanced Models for Tabular Data
Leakage-Safe Categorical Encoding for Financial ML intermediate
Categorical encoding becomes dangerous when a feature value quietly contains information from the target you are trying to predict.
Categorical encoding becomes dangerous when a feature value quietly contains information from the target you are trying to predict.
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References
Advances in Financial Machine Learning
Marcos Lopez de Prado
(2018)
— John Wiley & Sons
CatBoost: unbiased boosting with categorical features
Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin
(2019)
— arXiv:1706.09516 [cs]
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu
(2017)
— Curran Associates, Inc.