Collaborative filtering will be helpful. Regards, Vikash
On Wed, Dec 28, 2016 at 3:53 PM, Winson Lui <winson....@bwinparty.com> wrote: > HI, > > I have a historical dataset which tells who bought our products. This > dataset contains ID, Age, Gender and Salary. > I have another set of data which contains the four fields above. > How should I use R to calculate the probability of purchase of each > customer in the second dataset or whether they would buy our products (T/F)? > Should I use glm function? If yes, how should I approach this? > Thanks. > > Regards, > Winson Lui > Business Analyst > M: +44 (0) 79 1714 6247 > E: winson....@bwinparty.com<mailto:winson....@bwinparty.com> > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
