> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of j.joshua thomas > Sent: Tuesday, February 27, 2007 6:54 PM > To: [email protected] > Subject: [R] Datamining-package rattle() Errors > > Dear Group > > I have few errors while installing package rattle from CRAN > > i do the installing from the local zip files... > > I am using R 2.4.0 do i have to upgrade to R2.4.1 ? > > > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > > utils:::menuInstallLocal() > package 'rattle' successfully unpacked and MD5 sums checked > updating HTML package descriptions > > help(rattle) > No documentation for 'rattle' in specified packages and libraries: > you could try 'help.search("rattle")' > > library(rattle) > Rattle, Graphical interface for data mining using R, Version 2.2.0. > Copyright (C) 2006 [EMAIL PROTECTED], GPL > Type "rattle()" to shake, rattle, and roll your data. > Warning message: > package 'rattle' was built under R version 2.4.1 > > rattle() > Error in rattle() : could not find function "gladeXMLNew" > In addition: Warning message: > there is no package called 'RGtk2' in: library(package, > lib.loc = lib.loc, > character.only = TRUE, logical = TRUE, > > local({pkg <- select.list(sort(.packages(all.available = TRUE))) > + if(nchar(pkg)) library(pkg, character.only=TRUE)}) > > update.packages(ask='graphics') > > > On 2/28/07, Roberto Perdisci <[EMAIL PROTECTED]> wrote: > > > > Hi, > > out of curiosity, what is the name of the package you found? > > > > Roberto > > > > On 2/27/07, j.joshua thomas <[EMAIL PROTECTED]> wrote: > > > Dear Group, > > > > > > I have found the package. > > > > > > Thanks very much > > > > > > > > > JJ > > > --- > > > > > > > > > On 2/28/07, j.joshua thomas <[EMAIL PROTECTED]> wrote: > > > > > > > > > > > > I couldn't locate package rattle? Need some one's help. > > > > > > > > > > > > JJ > > > > --- > > > > > > > > > > > > > > > > On 2/28/07, Daniel Nordlund <[EMAIL PROTECTED]> wrote: > > > > > > > > > > > -----Original Message----- > > > > > > From: [EMAIL PROTECTED] [mailto: > > > > > [EMAIL PROTECTED] > > > > > > On Behalf Of j.joshua thomas > > > > > > Sent: Tuesday, February 27, 2007 5:52 PM > > > > > > To: [email protected] > > > > > > Subject: Re: [R] Datamining-package-? > > > > > > > > > > > > Hi again, > > > > > > The idea of preprocessing is mainly based on the > need to prepare > > the > > > > > data > > > > > > before they are actually used in pattern > extraction.or feed the > > data > > > > > > into EA's (Genetic Algorithm) There are no standard > practice yet > > > > > however, > > > > > > the frequently used on are > > > > > > > > > > > > 1. the extraction of derived attributes that is > quantities that > > > > > accompany > > > > > > but not directly related to the data patterns and may prove > > meaningful > > > > > or > > > > > > increase the understanding of the patterns > > > > > > > > > > > > 2. the removal of some existing attributes that > should be of no > > > > > concern to > > > > > > the mining process and its insignificance > > > > > > > > > > > > So i looking for a package that can do this two > above mentioned > > > > > points.... > > > > > > > > > > > > Initially i would like to visualize the data into > pattern and > > > > > understand the > > > > > > patterns. > > > > > > > > > > > > > > > > > <<<snip>>> > > > > > > > > > > Joshua, > > > > > > > > > > You might take a look at the package rattle on CRAN > for initially > > > > > looking at your data and doing some basic data mining. > > > > > > > > > > Hope this is helpful, > > > > > > > > > > Dan > > > > > > > > > > Daniel Nordlund > > > > > Bothell, WA, USA > > > > > > > > > > ______________________________________________ > > > > > [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< > > http://www.r-project.org/posting-guide.html> > > > > > and provide commented, minimal, self-contained, > reproducible code. > > > > > > > > > > > > > > > > > > > > > -- > > > > Lecturer J. Joshua Thomas > > > > KDU College Penang Campus > > > > Research Student, > > > > University Sains Malaysia > > > > > > > > > > > > > > > > -- > > > Lecturer J. Joshua Thomas > > > KDU College Penang Campus > > > Research Student, > > > University Sains Malaysia > > > > > > [[alternative HTML version deleted]] > > > > > > ______________________________________________ > > > [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 > > > and provide commented, minimal, self-contained, reproducible code. > > > > > > > > > -- > Lecturer J. Joshua Thomas > KDU College Penang Campus > Research Student, > University Sains Malaysia > > [[alternative HTML version deleted]] > > ______________________________________________ > [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 > and provide commented, minimal, self-contained, reproducible code. >
Joshua, Tim Churches has given you some good advice. Let me add that I probably should have pointed you to the URL below in my original post. You will need to install a couple other pieces of software to use rattle. Take a look at this guide, and in particular, the installation section. At the Togaware home page (I think) there is also some information about a Rattle mailing list. If you can't find it, you can email me and I will send you the URL. Good luck with your data mining. http://datamining.togaware.com/survivor/index.html Hope this is of some additional help, Dan Daniel J. Nordlund Research and Data Analysis Washington State Department of Social and Health Services Olympia, WA 98504-5204 ______________________________________________ [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 and provide commented, minimal, self-contained, reproducible code.
