Causal k-Means Clustering applies k-means to estimated counterfactual functions via plug-in and double machine learning bias-corrected estimators to identify subgroups with heterogeneous treatment effects and achieves root-n rates.
Then we have sup Q N(ϵ∥Fn∥Q,2,Fn,L 2(Q))≲ (c1 ϵ )c2ν′ for some universal constantsc 1,c 2 >0
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Causal K-Means Clustering
Causal k-Means Clustering applies k-means to estimated counterfactual functions via plug-in and double machine learning bias-corrected estimators to identify subgroups with heterogeneous treatment effects and achieves root-n rates.