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Train Gradient Boosting models that are both high-performance *and* Fair!

Results 17 fairgbm issues
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## Description When importing fairgbm on a mac I immediately get the following error message: ` OSError: dlopen(/python3.9/site-packages/fairgbm/lib_lightgbm.so, 0x0006): tried: '/python3.9/site-packages/fairgbm/lib_lightgbm.so' (not a mach-o file) ` Screenshot: I have tried...

bug
Important

## Summary Using a FairGBM model as a randomized classifier is described in detail in the FairGBM paper. However, this library only allows the use of the last FairGBM iterate...

enhancement
low priority
S effort

## Summary We should enable creating group-wise constraints on the percentage of positive predictions (a.k.a., predicted prevalence). This enables the popular _Demographic Parity_ fairness metric. **TODO** - [ ] Add...

enhancement
Important

The term `constraint_group` alludes to constrained optimization, but the main use-case for FairGBM is enhancing fairness and a better kwarg name should probably be chosen. Suggestions: - `sensitive_attributes` - `protected_attributes`...

enhancement

When using constrained_cross_entropy as an objective, FairGBM constrained_cross_entropy tries to use it as a metric (to report training progress). The issue here is that, currently, no such metric exists. Everything...

enhancement

We need to assess what are the side-effects of not having a proper ConstrainedCrossEntropy::ToString method. From a quick run through the code it seems the `ToString` method is used to...

bug
M effort
discovery

## Summary - Currently if we load a model from a file it will look for the "constrained_cross_entropy" objective function and will not find it. - We need to export...

enhancement
M effort
discovery

I just found out this file [helpers/parameter_generator.py](https://github.com/feedzai/fairgbm/blob/main-fairgbm/helpers/parameter_generator.py), which states at the beginning: > This script generates LightGBM/src/io/config_auto.cpp file with list of all parameters, aliases table and other routines along with...

low priority
S effort

According to our `perf` and `valgrind` benchmarks, a large percentage of CPU time is spent on synchronization of separate threads during training. The net outcome of multi-threading is still positive,...

enhancement
low priority
M effort
discovery

Including: - Getting started (install and run) - Minimal examples (load BAF and train a model in a 4-5 lines code example) - Detail FairGBM-specific parameters - Detail inner workings...

documentation
enhancement
Important
M effort