September 2018
Intermediate to advanced
472 pages
12h 2m
English
book
Python Data Science Essentials - Third Edition
by Alberto Boschetti, Luca Massaron, Pietro Marinelli, Matteo Malosetti
Content preview from Python Data Science Essentials - Third Edition
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CatBoost
In July 2017, another interesting GBM algorithm was made public by Yandex, the Russian search engine: it is CatBoost (https://catboost.yandex/), whose name comes from putting together the two words Category and Boosting. In fact, its strongest point is the capability of handling categorical variables, which actually make the most of information in most relational databases, by adopting a mixed strategy of one-hot-encoding and mean encoding (a way to express categorical levels by assigning them an appropriate numeric value for the problem at hand; more on that later).
As explained in the paper DOROGUSH, Anna Veronika; ERSHOV, Vasily; GULIN, Andrey. CatBoost: gradient boosting with categorical features support
(https://pdfs.semanticscholar.org/9a85/26132d3e05814dca7661b96b3f3208d676cc.pdf ...
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