Causal Falling Rule Lists

Fulton Wang; Cynthia Rudin

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arXiv · 1510.05189

Causal Falling Rule Lists

Fulton Wang·Cynthia Rudin

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Abstract

A causal falling rule list (CFRL) is a sequence of if-then rules that specifies heterogeneous treatment effects, where (i) the order of rules determines the treatment effect subgroup a subject belongs to, and (ii) the treatment effect decreases monotonically down the list. A given CFRL parameterizes a hierarchical bayesian regression model in which the treatment effects are incorporated as parameters, and assumed constant within model-specific subgroups. We formulate the search for the CFRL best supported by the data as a Bayesian model selection problem, where we perform a search over the space of CFRL models, and approximate the evidence for a given CFRL model using standard variational techniques. We apply CFRL to a census wage dataset to identify subgroups of differing wage inequalities between men and women.

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Fulton Wang, Cynthia Rudin. 2017-07-05. Causal Falling Rule Lists. https://arxiv.org/abs/1510.05189

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