Tal Galili
Tal Galili
Using calude 3 opus In this rewritten version: The cvglmnet and related functions have been replaced with sklearn's LogisticRegression and GridSearchCV for model fitting and hyperparameter tuning. The choose_regularization function...
This is violating user expectation. E.g.: ``` weights_untrimmed = sample.adjust( variables=weighting_variables, method="rake", weight_trimming_mean_ratio=0, transformations=auto_recodes, ) ``` By expectation violation I mean, 1. there isn’t anything in the docs that suggests...
We suspect that when providing a feature that has mostly unique string values and some NaN values, then this might lead the ipw model to give just weights of 1....
Current output:  It could be better to make sure the lines of covars are next to each other. That the diagnostics of the weights include also the ESSP and...
After adjustment, the object doesn't show any information of interest about the adjustment used (e.g.: ipw, or Deff, etc.) Consider to update it a bit (at least for the statistics...
Formulaic is a high-performance implementation of Wilkinson formulas for Python. https://github.com/matthewwardrop/formulaic It's probably worth transitioning to it once it matures.
The Empirical Calibration package, developed by Google, provides a method to compute empirical calibration weights using convex optimization. This approach balances out the marginal distribution of covariates directly while reducing...
The current workflow of just calling `adjust` might not be the easiest API for general Python/sklearn users.
This issue is for anyone interested in tracking the task of changing the license of the balance package. If you have direct value in us making this change, please leave...