Re:The Unreasonable Effectiveness of Random Forests
by joe_the_user on Saturday September 19, 2015 @02:56PM
(#10245200)
Mmmm,
Yeah, as I understand it, the enthusiasm for deep learning comes because it scales well to truly huge data sets where most other machine learning algorithms tend to create artifacts of a similar size to the data in question.
That is to say that deep learning, random trees and SVMs all do approximately the same thing - non-linear regression, equivalently regression on a feature space, roughly drawing curves between two sets on huge dimensional space and using these curves for distinguishing objects.
Also - the linked paper giving all the actual details of the algorithm seems unresponsive.
Yeah, as I understand it, the enthusiasm for deep learning comes because it scales well to truly huge data sets where most other machine learning algorithms tend to create artifacts of a similar size to the data in question.
That is to say that deep learning, random trees and SVMs all do approximately the same thing - non-linear regression, equivalently regression on a feature space, roughly drawing curves between two sets on huge dimensional space and using these curves for distinguishing objects.
Also - the linked paper giving all the actual details of the algorithm seems unresponsive.
This link worked for me:
https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf