Uplift Modelling via Gradient Boosting
Bulat Ibragimov, Anton Vakhrushev
2024年份
4被引次数
摘要
The Gradient Boosting machine learning ensemble algorithm, well-known for its proficiency and superior performance in intricate machine learning tasks, has encountered limited success in the realm of uplift modeling. Uplift modeling is a challenging task that necessitates a known target for the precise computation of the training gradient. The prevailing two-model strategies, which separately model treatment and control outcomes, are encumbered with limitations as they fail to directly tackle the uplift problem.
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