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Did I just read a powerpoint presentation?
by syense 11y ago
Did I just read a powerpoint presentation?
- joe_the_user 11y agoYeah, the presentation format is annoying but argument is good, in fact, the argument is really important. Machine learning is about approximate reasoning but with no real guarantees of the approximation. Even if the approximation is usually very good, being occasionally bad can be "deeply problematic" when we don't have control over exactly how exactly the bad recommendations are created.
- shockzzz 11y agoIsn't that what confidence intervals are for?
- RMarcus 11y agoI'd say that's more what cost functions are for, but that is neither here nor there. I think the biggest takeaways are... 1) Machine learning in large software projects is complex because decisions made by one algorithm can influence the data of other algorithms, creating massive biasing. 2) Simple cross-validation / hold back methodology is limited as we expand what we want machine learning to be able to handle. Reason: big data is too big and "correctness" is difficult to evaluate for things like Q/A systems.
- joe_the_user 11y agoIndeed it is and machine learning not being "real statistics" but ad-hoc methodologies (based on statistics but not being statistics) doesn't give confidence intervals etc. Plus read the article/presentation. It goes into the issue with great depth and clarity.
- xyzzy123 11y agoIf we pick a silly thing like recommendations, they happen in a multidimensional space. Not only do we not know the right metrics, shape of the space or cost functions, our feedback is distorted by the actual recommendations we give!