causalml
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uber
Uplift modeling and causal inference with machine learning algorithms
**Environment (please complete the following information):** - OS: Mac OS M1 - Python Version: 3.8 - Versions of Major Dependencies absl-py 1.0.0 actionrules-lukassykora 1.1.23 astunparse 1.6.3 Bottleneck 1.3.4 cachetools 5.0.0...
Hi, thanks for this awesome toolbox for uplift modeling. I have data for one treatment and one control group and used XGBoost as a base regressor. I'm trying to compare...
Following the document (https://github.com/uber/causalml/blob/master/README.md), I've installed the causalml package with conda, and can successfully 'import caucalml' in python. But when I tried to run the code `from causalml.dataset import synthetic_data`...
I would like to execute only the prediction task on one server, but it seems like the casuml package must be installed. The casualml package is too large, is there...
After reading several paper about causal tree and uplift model, I found these two model quite similar. The difference is merely that causal tree use loss function for continuous treatment...
**Describe the bug** Hi, I met the bug when fitting an UpliftRandomForestClassifier with n_jobs=-1 ` joblib.externals.loky.process_executor._RemoteTraceback: """ Traceback (most recent call last): File "/usr/lib/python3.6/pickle.py", line 269, in _getattribute obj =...
I know we can get the direct prediction with clf.predict(X,t), but is there any way we can get the corresponding class probabilities, like the output of some sklearn classifier.predict_proba()?
https://devguide.python.org/#status-of-python-branches Also, allow pip's new dependency resolver to work by providing multiple dependencies in the same command. ## Proposed changes Describe the big picture of your changes here to communicate...
I have been looking at the codes and thinking of using sklearn's RandomSearchCV but looks like the fit function doesn't allow additional parameters to be passed in:(https://github.com/uber/causalml/blob/84ac51953fa892719a43b15cd9ca1735b13dd114/causalml/inference/meta/tlearner.py#L64) Has anyone tried...
Hi, I got again error with ImportError: Building module causalml.inference.tree.causaltree failed: ["distutils.errors.CompileError: command 'gcc' failed with exit status 1\n"] I also tried env3.6,3.7, and 3.8 but none of them enabled...
