welp, that's the kind of code an idiot would have on his luggage
My little rule of thumb is to inherit if the new implementation is a 'pure' over the inherited class. That is, I'm not introducing any _new_ changes to the state of the class.
Thanks. I think you are furthering the point of prediction vs. modeling, right? You can, after all, get a confidence rating for a model
I am not an expert and am still reading thru the article, but why is it such a strong dichotomy? Don't all predictive algorithm also assume a data model? for example aren't hidden Markov models, by assuming constant…
welp, that's the kind of code an idiot would have on his luggage
My little rule of thumb is to inherit if the new implementation is a 'pure' over the inherited class. That is, I'm not introducing any _new_ changes to the state of the class.
Thanks. I think you are furthering the point of prediction vs. modeling, right? You can, after all, get a confidence rating for a model
I am not an expert and am still reading thru the article, but why is it such a strong dichotomy? Don't all predictive algorithm also assume a data model? for example aren't hidden Markov models, by assuming constant…