CatBoost Part 1: Ordered Target Encoding

One of the defining features of CatBoost is its concerted effort to avoid data leakage at all costs. In this video, we'll see how it eliminates a potential threat in Target Encoding by ordering the data and encoding it sequentially. This ordered approach is central to everything CatBoost does and we'll see it again in Part 2 when we talk about how it builds trees.

NOTE: This StatQuest is based on the original CatBoost manuscript... arxiv.org/abs/1706.09516
...and an example provided in the CatBoost documentation...
catboost.ai/en/docs/concepts/algorithm-main-stages…

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0:00 Awesome song and introduction
1:56 A slight problem with k-fold target encoding
3:42 Ordered Target Encoding

Corrections:
4:09 It is also worth noting that if there were more than 2 target values, for example, if Loves Troll 2 could be 0, 1 and 2, then, when calculating the OptionCount for a sample with Loves Troll 2 = 1, we would include rows that had Loves Troll 2 = 1 and 2.

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