EconML
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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...
I got a scenario that have categorical but non-binary treatment (can up to five option). Does DML and its variances, or metalearner support such scenario? It seems DML assumes partial...
The following estimation works fine: ``` est = LinearDML(model_y = LinearRegression() , model_t = LogisticRegression() , discrete_treatment = True, random_state = 123) est.fit(y, T, X=None, W = W) ``` However...
The code seems to work well without setting inference='bootstrap', but I encounter an error when attempting to obtain inference using bootstrap when I use the example in Notebook or my...
#791 ought to allow missing data when inferencing if allow_missing = True, but currently an error is thrown when the inference data includes missing data. RE: below for a working...
Hi EconML Team, I used EconML **CausalForestDML** over **continuous Treatment**. Here are couple questions about APIs and background theories that I hope for further clarification. **For continuous Treatment** 1. How...
In https://github.com/py-why/EconML/blob/f170babe07796df877ccca9c44fd3f91b09d42fa/econml/grf/classes.py#L1020, it seems that the RegressionTree `_get_alpha_and_pointJ` method has a different function signature than the other `CausalForest` and `CausalIVForest`. Is this on purpose? Shouldn't it be a different order...
Hello! First of all, thank you for this amazing library, it's gorgeous. But in the process of research, I had several questions about the methodology and interpretation. Question 1: we...
When our nightly builds (which try to use updated versions of our dependencies compared to our "last known good" files) succeed, this set of changes will enable the build to...
i am using DML to inference， the DML model has finished， but what interpret the model, some error occured as followed: InvalidParameterError: The 'criterion' parameter of DecisionTreeRegressor must be a...
If one changes the categories and refits the final, nothing changes ```python est = LinearDML(discrete_treatment=True).fit(Y, T, X=X, cache_values=True) est.categories = [0, 1] est.refit_final() ``` The result doesn't use the categories...
