Thank you Lorenz.. Yes rules can not be consider machine learning as its a kind of hard coding and machine will not learn by itself..
<https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=icon> Virus-free. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=link> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> On Mon, Jan 22, 2018 at 7:35 AM, Lorenz Buehmann < [email protected]> wrote: > I've just some very minimal experience in machine learning and rule > processing... > > The important keywords here are "machine" and "learning" - if you > provide a set of rules, then there was no learning. Except by the human > who used his/her knowledge to make the rules - if it's done by a > "machine", then you can call this machine learning of such rules (e.g. > rule induction) and use the rules to "infer" data - not predict. The > rules are just a (human-readable) way to encode the machine learning model. > > But, it's off-topic for sure, thus, I will not go further into details. > > > Lorenz > > > On 21.01.2018 14:50, javed khan wrote: > > Hello > > > > I am not sure if the question is related to the jena group but I will > > appreciate the answer. > > > > I want to ask is it possible we take the functionality of machine > learning > > techniques (bayes algorithm, decision tree etc) using semantic web > rules. I > > dont know much about machine learning but I know it makes prediction > based > > on past experience/past data. > > > > Like we provide set of rules based on past data (if this, then that) and > > make predictions/optimizations. For instance, we want to make bug > > predictions in a software using Semantic rules, so is it possible?? > > > > Thank you > > > > <https://www.avast.com/sig-email?utm_medium=email&utm_ > source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=icon> > > Virus-free. > > www.avast.com > > <https://www.avast.com/sig-email?utm_medium=email&utm_ > source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=link> > > <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> > > > > >
