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> >
