I thought that maybe authors of books on R should be allowed (encouraged ?) to announce availability/revisions of their books via the R-packages list? For example I'd be very interested to have another look at Dr. Torgo's book when it becomes more complete and I'd appreciate a revision notice via the list.
Just a suggestion. Thanks, Vadim > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Luis Torgo > Sent: Wednesday, October 13, 2004 12:03 PM > To: Prof Brian Ripley > Cc: Vito Ricci; [EMAIL PROTECTED] > Subject: Re: [R] Statistical analysis of a large database > > On Tue, 2004-10-12 at 08:36, Prof Brian Ripley wrote: > > > Lu�s Torgo, Data Mining with R. Learning by case studies, Maggio > > > 2003 http://www.liacc.up.pt/~ltorgo/DataMiningWithR/ > > > > Please note that that reference is not about large > datasets, nor about > > `data mining' in the generally used sense. It has two studies, one > > incomplete, on linear regression (with 200 samples) and on > time series. > > I would like to add a few information on these incomplete > comments on the book I'm writing. The book is unfinished as > mentioned on its Web page. It has currently two reasonably > finished chapters: an introduction to R and MySQL and a case > study. As mentioned in the book, the first case study is > small by data mining standards (200 observations) and has the > goal of illustrating techniques that are shared by data > mining and other disciplines as well as smoothly introducing > the reader to R and its power. It addresses data > pre-processing techniques, data visualization, model > construction (yes, linear regression but also regression > trees), and model evaluation, selection and combination, so I > think it is a bit incorrect to say that it is about linear > regression that corresponds to 5 of the 50 pages of that chapter. > > The third (unfinished) chapter (2nd case study) is about > financial trading. It includes topics like connections to > data bases as well as many other components of a knowledge > discovery process. Among those components it includes model > construction that involves obviously time series models given > the nature of the data. The chapter will include other steps > like issues concerning moving from predictions into actions, > creation of variables from the original time series, etc.. It > is currently being re-written and I expect to upload soon a > new revised version of this chapter. > > The book will include at least two further cases studies that > will be larger. Still, I would note that the financial > trading case study is potentially very large, as it is a > problem where data is constantly growing. The final version > of that chapter addresses this issue of having a system that > is online in the sense that it is receiving new data in real > time (also known as mining data streams in the data mining field). > > I'm sorry for being so long, but I think it is dangerous to > try to resume around 200 pages of an unfinished work in two > lines of text. > > Still, all comments on this on going project are very well > welcome and I would like to take this opportunity to thank > all people that have been sending me encouraging comments/emails. > > Luis Torgo > > -- > Luis Torgo > FEP/LIACC, University of Porto Phone : (+351) 22 607 88 30 > Machine Learning Group Fax : (+351) 22 600 36 54 > R. Campo Alegre, 823 email : [EMAIL PROTECTED] > 4150 PORTO - PORTUGAL WWW : > http://www.liacc.up.pt/~ltorgo > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
