MBrouns
MBrouns
Currently, dag construction works by supplying a dataframe where rows are duplicated `n` times where `n / len(df)` is the probability of occuring: ``` study | hard | grade --...
X and y will have a different size after the outlier removal because we can't filter y in the pipeline
ValueError: equal_opportunity_score only supports binary indicator columns for `column`. Found values ['Black' 'White']
``` from sklearn.model_selection import cross_validate, StratifiedKFold from sklearn.metrics import precision_score, recall_score, make_scorer cross_validate( pipeline, X, y, scoring = { 'eq_op_colour': equal_opportunity_score('colour', positive_target='Yes'), 'eq_op_age': equal_opportunity_score('age', positive_target='Yes'), 'eq_op_sex': equal_opportunity_score('sex', positive_target='Yes'), 'precision': make_scorer(precision_score,...
I noticed that the 0.4.3 branch is supposed to have DRF Serializer support, which is a feature I'm looking forward to very much. While attempting to use that branch though...