Niels Bantilan
Niels Bantilan
Tables can be found here: https://www.bls.gov/cps/cpswktabs.htm
The purpose of this issue is to add support for stratified mean difference and normalized mean difference so that we can control for other explanatory (or confounding) factors that may...
DAEC is like #10, with a similar relabelling rule as ROC but re-assigns any prediction where classifiers disagree on the predicted label. For example, if the an observation was positively...
PRR as an optimization technique that extends the standard L1/L2-norm regularization method by adding a prejudice index term to the objective function. This term is equivalent to normalized mutual information,...
Sampling is composed of two methods: # Uniform Sampling - uniformly sample (with replacement) `n` observations from each group, where `n` is the expected size of that group assuming a...
Reweighting takes a dataset `D` and assigns a weight to each observation using conditional probabilities based on target labels and protected class membership. `s1` - disadvantaged group `s2` - advantaged...
# Benchmark classifiers Train models with the following specifications using the [german_credit dataset](https://github.com/cosmicBboy/themis-ml/blob/master/themis_ml/datasets/datasets.py#L28) ## Models - logistic regression - random forest - svc - neural net ## Feature Sets -...
Stub issue for this potential integration: https://www.getdaft.io/