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It's often the case that we precompute a bunch of Distributions, but then need some subset of that for use as a function argument. For example we might have:
and we'd want to call cross_validated_scores(metric, folds, predictions), but since the metric takes a MarginalDistribution and our predictions are JointDistributions things don't work out gracefully.
The current approach is to specialize each function that needs to do this sort of conversion (see cross_validated_scores), but ideally we'd be able to set up a set of conversion methods that would let us do:
JointDistribution joint;
MarginalDistribution x = joint;
The text was updated successfully, but these errors were encountered:
It's often the case that we precompute a bunch of Distributions, but then need some subset of that for use as a function argument. For example we might have:
and we'd want to call
cross_validated_scores(metric, folds, predictions)
, but since themetric
takes aMarginalDistribution
and our predictions areJointDistribution
s things don't work out gracefully.The current approach is to specialize each function that needs to do this sort of conversion (see
cross_validated_scores
), but ideally we'd be able to set up a set of conversion methods that would let us do:The text was updated successfully, but these errors were encountered: