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>I question this meme that deep learning has less mathematical elegance or interpretability than other machine learning model. It's simply not true. I know, ri
by kefka 9y ago
>I question this meme that deep learning has less mathematical elegance or interpretability than other machine learning model. It's simply not true.
I know, right? Like, take this model I trained this morning. Here's the parameters it learned:[0.230948, 0.00000000014134, 0.1039402934, 0.000023001323, 0.00000000000005]
I mean, what's "black-box" about that, really? You can instantly:
(a) See exactly what the model is a representation of.
(b) Figure out what data was used to train it.
(c) Understand the connection between the training data and the learned model.
It's not like the model has reduced a bunch of unfathomably complex numbers to another, equally unfathomable. You can tell exactly what it's doing- and, with some visualisation, it gets even better.Because then it's a curve. Everyone groks curves, right?Right, you guys?
/s obviously.
- p1esk 9y agoI don't know what model you trained but if it only needs 5 parameters it's quite possible that you can figure out the corresponding features, and remove your sarcasm tags.
- YeGoblynQueenne 9y agoIt's perfectly possible to train a deep neural model with millions of features that outputs a vector of a handful of values, or even just a scalar. That's actually one of their strengths. [Full disclosure: that comment was originally mine from a different thread; I'm not affiliated with the OP in any way.]
- kefka 9y agoYes indeed. Your comment was sarcastically perfectly succinct and to the point. And it left a mark on me as being the best way to get across this "magic math" stuff encroaching into computer science. It does appear to be a very powerful tool, but with absolutely no introspection or any way to validate or invalidate content. Best one can hope, is that the dataset has no inherent biases ~ but even that's no claim the algo won't create a layer to make the biases, and then directly chose on biases. I probably should have cited it (was on mobile, but oh well :/ ). Well, I'll do it now: https://news.ycombinator.com/item?id=14219450 https://news.ycombinator.com/item?id=14219450 If anything, please consider this copy/edit as a sign of respect, and not of mockery :)
- YeGoblynQueenne 9y agoNo worries. It's all good :)
- p1esk 9y agoAre you confusing parameters with outputs?
- YeGoblynQueenne 9y agoWell, the numbers you get in the output are function parameters.