causalml
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uber
Uplift modeling and causal inference with machine learning algorithms
## Proposed changes This PR is mainly about causal trees support. * The architecture of a causal tree implementation was moved to a more modular approach: 1. `BaseCausalDecisionTree` inherits everything...
**Describe the bug** I am trying to install causalml package both using pip and from source following these instructions: https://causalml.readthedocs.io/en/latest/installation.html Unfortunately I cannot succeed with building wheel for causalml (screenshot...
Hello, I have been following one of the examples [(here)](https://github.com/uber/causalml/blob/master/examples/feature_interpretations_example.ipynb) and I see the meta learners have a `. get_shap_values` and `plot_shap_values` methods for SHAP values. Also, I think they...
**Describe the bug** Error while installing causalml libaray in Databricks runtime 9.1 **To Reproduce** !pip install causalml **Expected behavior** ```` Collecting causalml Using cached causalml-0.12.3.tar.gz (406 kB) Preparing metadata (setup.py)...
**Description** On first attempt, meta-learners perform great: lift and gain curves look reasonable and I can identify groups with stark heterogeneous effects. Whenever the notebook is run again, cannot to...
**Is your feature request related to a problem? Please describe.** The Interaction Tree (IT) (Su et al. 2009) and Conditional Interaction Tree (CIT) (Su et al. 2012) have been proposed...
Hello. It is really not a request for a feature neither it is a bug. I was looking for a package to do heterogeneous treatment effects of different treatments and...
Hello. I followed your example notebook for Uber Targetting Optimization (slide is [here](https://drive.google.com/file/d/1QJJUCo4LH5kGQP3kaJlG1RdhjhaJWp-5/view) and notebook is [here](https://colab.research.google.com/drive/1fnZEHIAcNxrvSxFrlO1hRTHO7sazXbo0?usp=sharing) ) for finding the best users to target to minimize the advertising cost....
hello, I use UpliftRandomForestClassifier to do a uplift model. I am confused about the result. here is my result.  is it reasonable that my auuc is greater than 1...
**Describe the bug** Following the example, when running the code (meta_learners_with_synthetic_data)  I encounter error:  show estimate_ate() got an unexpected keyword argument 'pretrain' **Environment (please complete the following information):**...
