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ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goal...
Hi! Anyone knows of existing papers or methods, that applies Double ML to highly imbalanced dataset with, for example, a dataset with less than 1% samples being positively treated while...
Hi, without giving too much information we are using the DML-RF with this CausalAnalysis function to get out point estimates for a given treatment. The **outcome is market share** and...
Adressing https://github.com/microsoft/EconML/issues/557 Just did ForestDRLearner to see if you agree with the way I'm doing it, will add the others if so. Is there a reason you don't support dowhy...
It's quite hard to guess the 'right' number of trees for a particular estimator, and a full-on hyperparameter search is quite expensive. Would be great to have an early stopping...
That seems rather large, especially as in CausalForestDML the default is `n_estimators=100`, and the ForestDRLearner with n_trees=1000 can take quite a while to fit. Also for example in XGBoost, also...
Hi, the causal_forest function of the R grf package has a very useful option 'clusters', that allows for cluster-robust estimation. I wonder if there is any plan to implement this...
Hi, I tried to use the deepiv function with the microsoft tutorial and find the loss value is negative at first and then turns to positive. Here are also two...
Dear EconML support team. I am using Causal Forests for calculating CATEs, and the main issue I am facing is that confidence intervals calculated (CIs) are too large with my...
I am fitting a CausalForestDML model on an Azure Machine Learning compute instance with 32 cores. My dataset has ~3 million records and ~60 variables. Surprisingly, fitting speed decreases with...
> (i.e. there is no unobserved variable not included in X, W that simultaneously has an effect on both T and Y) All unobserved variables that have an effect on...
