Hi Gabriel, you can find the data here
https://github.com/STEllAR-GROUP/hpxML Best, Patrick On 27/02/18 10:45 AM, Gabriel Laberge wrote: > Hi, > I have an idea for a machine learning project and I need some feedback. > > In the article [0] https://arxiv.org/pdf/1711.01519.pdf A multinomial > regression is used to find the optimal chunk size and prefetching > distance. However, a multinonial regression is actually a > classification algorithm so it can only choose values from a finite > set. This allows to get a pretty good value for the output variables > but it isn't the 'optimal' values. I propose using a regression > algorithm instead that could output continuous values.The first one > that comes to my mind is Nearest Neighbor Regression but I'm sure > there are other ones that could be used. This would allow the > regression to output the 'optimal' value of chunk size and prefetching > distance instead of choosing the best one from a finite set of values. > > Then, I would like to implement this in HPX as an alternative to the > multinomial regression and compare the performance of both algorithms. > This will allow me to see if such a precision is really needed on > chunk size and prefetching distance or if a classification algorithm > is good enough. To be able to compare both algorithm, I assume I will > have to use the same data that was used in [0]. > > What are your thought? > Thank you. > Gabriel > > > > > _______________________________________________ > hpx-users mailing list > [email protected] > https://mail.cct.lsu.edu/mailman/listinfo/hpx-users > _______________________________________________ hpx-users mailing list [email protected] https://mail.cct.lsu.edu/mailman/listinfo/hpx-users
