Survival regression with AFT model in XGBoost | AISC

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=HuWRnzgGuIo


Duration: 44:13
1,965 views
34

Speaker(s): Hyunsu (Philip) Cho, Avinash Barnwal

Find the recording, slides, and more info at https://ai.science/e/aft-xg-boost-survival-regression-with-aft-model-in-xg-boost--YoUycmJCU0AijtV4s4rd

Motivation / Abstract
In marketing modeling, time-to-event models occupy a very prominent role in deciding whom to target during a campaign and, just as importantly, when to target. In the paper serving as the foundation for this talk, the speakers (along with Dr. Toby Hocking) have developed a novel adaptation of an Accelerated Failure Time (AFT) model that integrates with XGBoost. This, in turn, paves the way for implementations of tree-based models that are able to offer support for survival regression. Furthermore, use of NVIDIA GPUs allows for a substantial speedup in training times.



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