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Based on the inference/meta/xlearner.py fit function docstr when p (propensity score) is None then ElasticNetPropensityModel() is used to generate the propensity scores. However, it appears to me that…
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Hi I have a question regarding to the Code of the Package.
I have tried to implement the Hillstrom (RCT) data set in CausalLift, but somehow the results look a bit weird. I splitted the dataset into …
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Dear team,
the Whitepaper to causalml states that
> the current implementation of the uplift modeling is encouraged to be applied to the data from the randomized experiment.
> Applications to ob…
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Is there any example code for feature selection? I'm using UpliftRandomForestClassifier
I saw this , but still not sure how to do filter works...
Feature Selection Methods for Uplift Modeling , http…
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**Is your feature request related to a problem? Please describe.**
Exhausted all cited research, documentation, and also tried inspecting the code yet I am still struggling to understand if causalM…
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I'm new in field of Causality and I would like to use your package for my current project.
I was searching for a python package based on Judea Pearl's graphical models, the I found your package. I a…
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We have a problem with creation of an explainer with package dalex. We are dealing with uplift modeling. We calculate uplift based on function calc_uplift_filled, which is based on xgboost model. Our …
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Hi,
I would like to ask you some questions about your codes (Causallift).
My first question is that: what is the advantages of using Causallift? I mean If we have a binary treatment then I use…
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Hey ! I was wondering if I could contribute to scikit-uplift by including an **additional parameter to the SoloModel class.**
According to the paper (Lo, Victor. 2002.
The True Lift Model - A Nov…
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In the traditional supervised machine learning to evaluate prediction accuracy we use actual values of the response variable. In the heterogeneous treatment effect modeling, ground truth is not availa…