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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...
@kbattocchi Hello Keith, I hope you are doing well. I wanted to understand a couple of unique properties of econml that apply to many estimators (I am looking right not...
Added additional functionality to the DRTester validation class to include uniform confidence bands (both two- and one-sided) for uplift curve plots, calculated via the multiplier bootstrap. Modified files are: -...
@kbattocchi Hi Keith, How would you recommend handling a case where we know the true treatment probabilities? I'd prefer to use them to avoid having to fit the model_propensity (in...
Seems that one can run into ZeroDivisionErrors when using NonParamDMLIV. Reproduction code below. Note, the error is not consistent. You may have to run it multiple times before getting the...
Shap Bug
I'm getting a numpy error when I'm running shap. I'm using: econml 0.14.1 numpy 1.24.3 ```AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin...
Hello, I am a fan of EconML, but I will be extremely happy if you develop an ML model to perform an estimation of overall, direct, and indirect causal effects...
Hi everyone, If we do the example from the `DynamicDML` class ```Python from econml.panel.dml import DynamicDML np.random.seed(123) n_panels = 100 # number of panels n_periods = 3 # number of...
Hi, I'm building a causal forest with binary outcome and binary treatment. I have sufficient observations (over 100K) for two groups, but the model doesn't seem to work well because...
Can we compare model.score_ values across different model types? (DML, DRL, linear vs forests, etc.)
I'm getting differences in .score_ values of 10x, between simple data sets and small models using LinearDRLearner vs LinearDML. So I'm seeing 21,000 for LinearDRLeaner and 2,000 for LinearDML. Is...
All of the use cases of causal modeling I'm involved include a geographic component in which it's critical to be able to simultaneously estimate both parent-level insights (like Total US)...