similar to: Discretization of numeric attributes

Hey, I'm looking for a function which provides a supervised Fayyad & Irani discretization (MDL). I've already found RWeka which has such a function. But is there anything else? I'd prefer to use sth lighter in my own package. Regards, Peter

I've been trough the R documentation for about half an hour and it's not clear to me how to do this: I need to format to character a series of integers from 1 to 1000, and I like them to look like "0001" "0002", "0059", "0123" and so on. Padded with zeroes to have four digits. Cheers! Mario. r-help-request at r-project.org wrote: > Send

Hi, Is anybody using Copula package for fitting copulas to own data? I have two marginals Log Normal with (parameters 1.17 and 0.76) and Gamma ( 2.7 and 1.05) Which package I should use to fit Gumbel and Clayton Copulas? Thanks, fayyad [[alternative HTML version deleted]]

Dear all, First, sorry for all that noise. I know you guys *just don't care*TM, but this requires some clarification. I won't say more than what's in this email. The VMKit paper dates from early 2008. It compares VMKit with pnet 0.7.4 and not the latest release (0.8.0) because we were not able to get any information to build it correctly at the time; the website that hosted

Dear all, This new version of the paper at: http://hal.archives-ouvertes.fr/docs/00/36/53/37/PDF/RR-6799.pdf got ride of libJIT. Now my question is the how scientific is this research and research paper if instead of using libJIT and Portable.NET JIT: authors of "VMKit: a Substrate for Virtual Machines by Nicolas Geoffray — Gaël Thomas— Charles Clément —Bertil Folliot — Gilles

Hi Chris, Just in case that this information does not get corrupted I want to point to the issue: In http://llvm.org/devmtg/2008-08/Geoffray_VMKitProject.pdf it is on page 21: "VMKit, Mono, PNet", Array bounds checks. In http://hal.inria.fr/docs/00/35/45/77/PDF/RR-6799.pdf it is on page 17: "We compare N3 with Mono [9] version 1.2.6, and PNet version 0.7.4 [2], which uses

On Mar 2, 2009, at 8:25 AM, Kirill Kononenko wrote: > Hello Dear LLVM Developers and Users Hi Kirill, Please talk to Nicholas about this, thanks! -Chris > > > I would like to complain about scientific inaccuracy of the paper > http://hal.inria.fr/docs/00/35/45/77/PDF/RR-6799.pdf written by > Nicolas Geoffray, Gaël Thomas, Charles Clément, Bertil Folliot, Gilles > Muller

Hello So how did it happen that the only project which was a candidate for libJIT Summer of Code in GNU, with the same title got selected in LLVM? Does it mean that the same genius idea came to two minds? Thanks, Kirill -- http://code.google.com/p/libjit-linear-scan-register-allocator/

Hi, I am using some classifiers in RWeka packages and met a couple problems. (1) J48 implements C45 classifier, the C45 should be able to handle missing values in both training set and test set. But I found the J48 classifier can not be evaluated on test set with missing values--it just ignore them. (2) The ensemble classifiers in RWeka such as bagging and boosting: there is a

Hello Dear LLVM Developers and Users I would like to complain about scientific inaccuracy of the paper http://hal.inria.fr/docs/00/35/45/77/PDF/RR-6799.pdf written by Nicolas Geoffray, Gaël Thomas, Charles Clément, Bertil Folliot, Gilles Muller and presentation done by Nicolas Geoffray on LLVM conference supported by Google: http://llvm.org/devmtg/2008-08/Geoffray_VMKitProject.pdf They provide

Hi, there: I have a variable whose distribution is far from normal and its qqnorm is S-shape, like a logisitic plot. My purpose is to discretize it into 2 or 3 classes. (basically, a transformation from quantative to discrete). I am wondering if there is a good way to do that. thanks, Ed

Dear All, I'm now working on Archimedean copulas and try to test the goodness of fit. Which packages I should use? I have Clayton copula with parameter (5.35) and Frank (19.5). I found this build function wrote by Yan and Ivan via R Packages, but I'm not sure the matrix for x? Please advice. e.g gofCopula(claytonCopula(1),x) Thank you Regards, Fayyad [[alternative HTML version

Dear r-users, Any such a way that we can compute SPI using kernel function (nonparametric approach) without assuming any parametric distributions? Any existing package for above method using R? Thank you for your help. Fayyad [[alternative HTML version deleted]]

Hi All, Are there any package to check the GOF for nonparametric copulas using R? Fayyad [[alternative HTML version deleted]]

On Apr 20, 2009, at 12:42 PM, Kirill Kononenko wrote: > Dear all, > > > This new version of the paper at: > > http://hal.archives-ouvertes.fr/docs/00/36/53/37/PDF/RR-6799.pdf > > got ride of libJIT. Now my question is the how scientific is this > research and research paper if instead of using libJIT and > Portable.NET JIT: > authors of "VMKit: a Substrate

Hi guys, I'd like to thank you ahead of time for any help that you can offer me. I'm kind of stuck trying to do this. I have a data frame with dates and values (note: only two columns shown): head(test) date value stop 1 01/02/05 100 12/01/07 2 07/16/05 200 12/01/07 3 12/20/05 150 12/01/07 4 04/01/06 250 12/01/07 5

Hi Chris How does this has nothing to do with llvm? Is not the VMKit project an official part of LLVM? Thanks, Kirill -- http://code.google.com/p/libjit-linear-scan-register-allocator/

Hi, everyone, This is a little silly, but I cant figure out the algorithm behind lm.fit function used in the context of promax rotation algorithm: The promax function is: promax <- function(x, m = 4) { if(ncol(x) < 2) return(x) dn <- dimnames(x) xx <- varimax(x) x <- xx$loadings Q <- x * abs(x)^(m-1) U <- lm.fit(x, Q)$coefficients d <-

Dear R-help, I am looking for ideas and presentations of new and advanced data visualization methods. As an example of what I am searching for, the 'Many Eyes' pages at http://manyeyes.alphaworks.ibm.com/manyeyes/ may provide a good paradigm. I would be interested even if it will not be easy to implement such examples in R, e.g. because of the interactive nature of these graphical

Given a data frame with a continuous variable and a factor. I would like to generate a histogram of the continuous variable, where each bar is filled with different colors according to the percentage of factor values falling into this region of the continuous variable. I looked into packages like 'lattice' and 'ggplot2'. Searching R-help revealed that 'histogram' is