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And as coffeemug points out on that post as you (generally) cannot guarantee the independence of the variables you are changing to influence user behaviour. Thi
by hartror 15y ago
And as coffeemug points out on that post as you (generally) cannot guarantee the independence of the variables you are changing to influence user behaviour. This makes the multiarmed bandit unsuited to the task the article espouses.
- noelwelsh 15y agoThen it also makes A/B testing unsuited to the task... Independence is a useful assumption, as it allows more tractable algorithms. It is a correct assumption? No, obviously not, but it close enough to correct that the results you get from it are good. People have made plenty of money using A/B testing, which also makes an independence assumption, and people will make plenty of money using bandit algorithms. The only difference is they'll make more money using bandit algs.
- pgroves 15y agoThis is true in any practical machine learning problem and it doesn't cause as much of a problem as theoreticians would have you believe. Having independent variables, or detecting and accounting for all dependencies, will typically lead to a better result. But when there are dependencies it merely degrades accuracy. It does not destroy the accuracy altogether. If you were to try to address every possible independence assumption in practice, you'd never get through a research project, let alone get a real product out the door as this company has done. [Edit: syntax]