thiru_2718 t1_j7o82dn wrote on February 8, 2023 at 5:22 AM

Nice work! There's some intriguing sections here that I definitly want to take a look at.

Quick question, with regards to this quote in the preface: "For instance, regression techniques ... are presented as a single method, without using advanced linear algebra."

Are you referring to Generalized Linear Models? I don't see any references to GLMs, in my brief skim, but I can't think of how else regression can be presented as a single method.

Also, is there any place where we can get a preview of "Shape Classification and Synthetization via Explainable AI" section?

MLRecipes OP t1_j7oec5y wrote on February 8, 2023 at 6:29 AM

No, it does encompass GLM but the technique also works when there is no response (you then need to put a constraints on the parameter) or with truly non linear models with time series examples in the book. Or for particular clustering cases. I like to call it unsupervised regression, but a particular case with appropriate constraint on the parameters corresponds to classic regression. More about it here. As for shape classification, see here.