Re:BlackRock shelves unexplainable AI liquidity models
by conjectures on Tuesday November 13, 2018 @01:43PM
(#18443550)
In general they don't in the sense of being fully Bayesian.
The mental gymnastics are that:
- The objective function of the neural net was a likelihood.
- The prior was improper.
In which case the net is a MAP estimate.
A MAP estimate will not give you good uncertainty quantification. Given the application to risk modelling, this seems unlikely to be a trivial departure from a fully Bayesian method.
The mental gymnastics are that: - The objective function of the neural net was a likelihood. - The prior was improper. In which case the net is a MAP estimate.
A MAP estimate will not give you good uncertainty quantification. Given the application to risk modelling, this seems unlikely to be a trivial departure from a fully Bayesian method.