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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 6: AAAI-22 Technical Tracks 6

Imbalance-Aware Uplift Modeling for Observational Data

February 1, 2023

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Authors

Xuanying Chen

Ant Group


Zhining Liu

Ant Group


Li Yu

Ant Group


Liuyi Yao

Alibaba Group


Wenpeng Zhang

Ant Group


Yi Dong

Ant Group


Lihong Gu

Ant Group


Xiaodong Zeng

Ant Group


Yize Tan

Ant Group


Jinjie Gu

Ant Group


DOI:

10.1609/aaai.v36i6.20581


Abstract:

Uplift modeling aims to model the incremental impact of a treatment on an individual outcome, which has attracted great interests of researchers and practitioners from different communities. Existing uplift modeling methods rely on either the data collected from randomized controlled trials (RCTs) or the observational data which is more realistic. However, we notice that on the observational data, it is often the case that only a small number of subjects receive treatment, but finally infer the uplift on a much large group of subjects. Such highly imbalanced data is common in various fields such as marketing and medical treatment but it is rarely handled by existing works. In this paper, we theoretically and quantitatively prove that the existing representative methods, transformed outcome (TOM) and doubly robust (DR), suffer from large bias and deviation on highly imbalanced datasets with skewed propensity scores, mainly because they are proportional to the reciprocal of the propensity score. To reduce the bias and deviation of uplift modeling with an imbalanced dataset, we propose an imbalance-aware uplift modeling (IAUM) method via constructing a robust proxy outcome, which adaptively combines the doubly robust estimator and the imputed treatment effects based on the propensity score. We theoretically prove that IAUM can obtain a better bias-variance trade-off than existing methods on a highly imbalanced dataset. We conduct extensive experiments on a synthetic dataset and two real-world datasets, and the experimental results well demonstrate the superiority of our method over state-of-the-art.

Topics: AAAI

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HOW TO CITE:

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu Imbalance-Aware Uplift Modeling for Observational Data Proceedings of the AAAI Conference on Artificial Intelligence (2022) 6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu Imbalance-Aware Uplift Modeling for Observational Data AAAI 2022, 6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu (2022). Imbalance-Aware Uplift Modeling for Observational Data. Proceedings of the AAAI Conference on Artificial Intelligence, 6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. Imbalance-Aware Uplift Modeling for Observational Data. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. 2022. Imbalance-Aware Uplift Modeling for Observational Data. "Proceedings of the AAAI Conference on Artificial Intelligence". 6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. (2022) "Imbalance-Aware Uplift Modeling for Observational Data", Proceedings of the AAAI Conference on Artificial Intelligence, p.6313-6321

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu, "Imbalance-Aware Uplift Modeling for Observational Data", AAAI, p.6313-6321, 2022.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. "Imbalance-Aware Uplift Modeling for Observational Data". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. "Imbalance-Aware Uplift Modeling for Observational Data". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 6313-6321.

Xuanying Chen||Zhining Liu||Li Yu||Liuyi Yao||Wenpeng Zhang||Yi Dong||Lihong Gu||Xiaodong Zeng||Yize Tan||Jinjie Gu. Imbalance-Aware Uplift Modeling for Observational Data. AAAI[Internet]. 2022[cited 2023]; 6313-6321.


ISSN: 2374-3468


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