4 ms·
I was just listening to that podcast yesterday and loved the way he presented this information. I know next to nothing about NNs but I could pretty much follow
by dasboth 11y ago
I was just listening to that podcast yesterday and loved the way he presented this information. I know next to nothing about NNs but I could pretty much follow everything that he said (from an intuitive sense, anyway, if not a technical one).
This "magic" of converging networks reminds me of how ensemble methods, such as random forests, are effective but people aren't sure why. There's certainly (AFAIK) no theoretical grounds to say that a bunch of random decision trees should yield universally good results.
- mziel 11y agoThere are. It's all about variance reduction. See the Breiman's paper on Bagging. There's nothing special about random forest though (apart from the fact that a decision tree is a good learner, because of the nonlinearities for example), you can you ensemble learning with any "basic" learner.
- dasboth 11y agoI read Breiman's random forest paper, but I'll give his others a read too. Does the variance reduction effect apply to any ensemble method then?