4 ms·
> doesn't quite cut it I think the underlying assumption here is that some approaches are too simple to "cut it", ie to be called machine learning. And eg PCA
by jmmcd 7y ago
> doesn't quite cut it
I think the underlying assumption here is that some approaches are too simple to "cut it", ie to be called machine learning. And eg PCA is too simple, and so should be excluded, and perhaps categorised as "just" statistics or linear algebra depending on your point of view. But in my view, it's better to let go of this view which implicitly hypes ML in a damaging way. F = ma is still physics, even if simple. k-NN and PCA are still ML.
- CrazyStat 7y agoEh, I disagree. Not from a normative point of view, but from a descriptivist one. Most people don't consider doing a PCA to be machine learning. I'm a statistician, not a machine learning guy. PCA is a great statistical method. But doing a PCA and calling it machine learning seems a tad misleading.
- jmmcd 7y agoWell, I certainly agree that many people use ML in this way. But to me it's just bad terminology. The thing that happens during ML -- the L part -- must be the same as what happens during statistical learning. Many (sophisticated) ML algorithms are statistical in nature, so there is nothing there that stops simple stat-learning algorithms from being ML algorithms. And there is nothing in the terminology that says ML has to be sophisticated relative to stat learning.