mr_uplift
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Ibotta
Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and multiple responses
Hi, I have a SIGKILL(-9) memory problem on a ~3millions rows, ~150 columns dataset with a 12CPU 128g memory resources, with unique discrete treatment (T) and discrete target (y). I...
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.4.1 to 2.9.3. Release notes Sourced from tensorflow's releases. TensorFlow 2.9.3 Release 2.9.3 This release introduces several vulnerability fixes: Fixes an overflow in tf.keras.losses.poisson (CVE-2022-41887) Fixes a...
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Hello, the repo states that multiple treatments (along with multiple outcomes) are enabled. In my case I have 3 treatments which are continuous such as Price, discount, and quality. I...
@samcarlos Hi Sam, I am trying to install MR Uplift and noticed some issues: - pip install issue due to sklearn. Here is the error code: ``` × python setup.py...
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.4.1 to 2.11.1. Release notes Sourced from tensorflow's releases. TensorFlow 2.11.1 Release 2.11.1 Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting...
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.4.1 to 2.12.1. Release notes Sourced from tensorflow's releases. TensorFlow 2.12.1 Release 2.12.1 Bug Fixes and Other Changes The use of the ambe config to build and...