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...
Hi, I have a couple of questions for [Case Study - Customer Segmentation at An Online Media Company](https://github.com/microsoft/EconML/blob/main/notebooks/CustomerScenarios/Case%20Study%20-%20Customer%20Segmentation%20at%20An%20Online%20Media%20Company.ipynb) 1. In the true te estimate part, why was it not just...
Hey, I have multi treatments and I want to use CausalForest but with your wrapper MultiOutputGRF on top. I do not have confounding in my data so I do not...
When using BootstrapInference to estimate the whole confidence interval, The standard error of the current version is to calculate the variance of each sample according to the ITE value of...
When I use the CausalAnalysis interpreter, unlike the example, there are no categorical variables in my data, so how do I handle the categorical parameter in CausalAnalysis interpreter? AssertionError: categorical...
Hi Keith, @kbattocchi I had a follow-up question on the SingleTreePolicyInterpreter (causal forest) Interpreter in general. My questions are: 1. If I have 3 Y-variables (i.e. sales, retention, session duration),...
``` OS Architecture: ``` Operating System: Ubuntu 20.04.4 LTS Kernel: Linux 5.15.0-53-generic Architecture: x86-64 ``` With a DataFrame of size `(rows, columns) = (9000, 102)`, the `fit` method I often...
Hello @kbattocchi First of all thank you for your package, extremely useful. I have several questions about it. First let me introduce some context. My goal is to find among...
The migration to the v4 version of the artifact API has somewhat broken rerunning tests for a PR in some scenarios because now artifacts are scoped to the attempt, but...
Hi All, I have a couple of questions when I am using the CausalForest DML, any help is super much appreciated!! 1. When I am evaluating the performance of the...
Hi @kbattocchi , This [paper](https://pubmed.ncbi.nlm.nih.gov/28430842/) presents a method to partially correct for residual confounding in time series, including in the model a negative control exposure (the value of the exposure...
