[R] Announcing books on R - policy {was "Statistical analys..."}
Martin Maechler
maechler at stat.math.ethz.ch
Fri Oct 15 12:31:42 CEST 2004
>>>>> "Vadim" == Vadim Ogranovich <vograno at evafunds.com>
>>>>> on Thu, 14 Oct 2004 10:50:08 -0700 writes:
Vadim> I thought that maybe authors of books on R should be
Vadim> allowed (encouraged ?) to announce
Vadim> availability/revisions of their books via the
Vadim> R-packages list?
Well, most good *) books on R nowadays have a (usually small) R
package going along, for datasets and some own functions.
*) One notable current exception: Uwe Ligges book
__in German__ >> http://www.statistik.uni-dortmund.de/~ligges/PmitR/
But maybe he'll change that too.
Vadim> For example I'd be very interested to have another
Vadim> look at Dr. Torgo's book when it becomes more
Vadim> complete and I'd appreciate a revision notice via the list.
Hmm, I'm really reluctant to change the 'R-packages' policy,
particularly because it won't be necessary in general (see above).
Further note that we have the 'R Newsletter' with book reviews,
too.
Further comments are welcome.
Martin Maechler
Vadim> Thanks, Vadim
>> -----Original Message-----
>> From: r-help-bounces at stat.math.ethz.ch
>> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Luis Torgo
>> Sent: Wednesday, October 13, 2004 12:03 PM
>> To: Prof Brian Ripley
>> Cc: Vito Ricci; r-help at stat.math.ethz.ch
>> Subject: Re: [R] Statistical analysis of a large database
>>
>> On Tue, 2004-10-12 at 08:36, Prof Brian Ripley wrote:
>> > > LuÃs 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 : ltorgo at liacc.up.pt
>> 4150 PORTO - PORTUGAL WWW :
>> http://www.liacc.up.pt/~ltorgo
>>
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