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arXiv 2007.016202020-07cs.LGstat.ML

Team voyTECH: User Activity Modeling with Boosting Trees

Palaimon GmbH（Palaimon 有限公司）；Huawei Technologies Zurich Research Center（华为技术苏黎世研究中心）

Immanuel Bayer, Anastasios Zouzias

英文摘要：

This paper describes our winning solution for the ECML-PKDD ChAT Discovery Challenge 2020. We show that whether or not a Twitch user has subscribed to a channel can be well predicted by modeling user activity with boosting trees. We introduce the connection between target-encodings and boosting trees in the context of high cardinality categoricals and find that modeling user activity is more powerful then direct modeling of content when encoded properly and combined with a suitable optimization approach.

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