DAME-FLAME-Python-Package
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A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data
They look a little empty (sorry, don't know Jekyll) 
Bumps [nokogiri](https://github.com/sparklemotion/nokogiri) from 1.14.3 to 1.16.3. Release notes Sourced from nokogiri's releases. v1.16.3 / 2024-03-15 Dependencies [CRuby] Vendored libxml2 is updated to v2.12.6 from v2.12.5. (@flavorjones) Changed [CRuby] XML::Reader sets...
Also bumping Numpy to a more secure version
A number of small things: - Check the pe_frac things - Add paper citation, update names/contact email - Perhaps add the algorithm diagram from the paper somewhere too - (if...
When data set size goes to millions of rows and hundreds of features, it takes hours to run. Could there be ways to shorten the computing time?
The above mentioned Error occurred in the following line: model = dame_flame.matching.FLAME(adaptive_weights = 'ridgeCV' , repeats = True , verbose = 3) model.fit(holdout_data = df11 , treatment_column_name='AGE', outcome_column_name='DIAGNOSIS') result =...
As per discussion with @nehargupta via email, it'd be helpful if dame returned an analysis dataset. `results` is a start, but it drops treatment assignment and outcome, and the insertion...
When running with the adaptive_weights='decisionTreeCV' parameter, in late iterations, sometimes the error 'no object to concatenate' appears. It seems like users who see this error can avoid it by using...
look to see if the post_processing file for CATE and ATE and ATT is vulnerable to floating point rounding issues, and if true, how to resolve? Use a small 4...