Before my course on "big data and economics" at the University of Barcelona in July, I wanted to upload a series of posts on classification techniques, to get an insight on machine learning tools.
According to a common idea, machine learning algorithms are black boxes. I wanted to get back on that saying. First of all, isn't that also the case for regression models, like generalized additive models (with splines)? Do you really know what the algorithm is doing? Even the logistic regression. In textbooks, we can easily find math formulas. But what is really done when I run it in R?
from DZone.com Feed https://ift.tt/2spnALw
No comments:
Post a Comment