similar to: Is there any R package that contains Rusboost based on Adaboost.m2?

Hi Joey, Still the same message. I am running it from llvm-2.9/Debug/bin/clang -cc1 -ast-view ~/smd.c Is this where you were referring to? Best, Carlos Andrade http://carlosandrade.co 2012/6/9 Joey Gouly <joel.gouly at gmail.com> > You need to run the clang from the build directory. Something like > ./Debug+Asserts/bin/clang > > Joey > > > On 9 June 2012 22:52,

Just in case another person comes to get stuck on this on Mac OS: http://web.mit.edu/mfloyd/www/computing/mac/gv/ This link explains the process on getting gv installed since Xaw3d dependency even has a 'error' (actually missing few parameters) on a line that prevents code compilation that needs to be fixed before configuring and make it works. -- I have gv installed now and my bash

You need to run the clang from the build directory. Something like ./Debug+Asserts/bin/clang Joey On 9 June 2012 22:52, Carlos Andrade <carlosviansi at gmail.com> wrote: > Just in case another person comes to get stuck on this on Mac OS: > > http://web.mit.edu/mfloyd/www/computing/mac/gv/ > > This link explains the process on getting gv installed since Xaw3d > dependency

Just to add one more thing. I have been trying to install the gv on my mac os but I have not been successful either. The gv build requires xaw3d ( http://directory.fsf.org/wiki/Xaw3d ) which apparently has not been updated for quite few years and the download is not even available anymore. Carlos Andrade http://carlosandrade.co 2012/6/9 Carlos Andrade <carlosviansi at gmail.com> > Hi

Hi Joey, I think there is still something missing. I ignored the -j as you mentioned and saw on the documentation that to compile on debug mode I could do so using: $./configure --disable-optimized As a result by the end I compiled llvm2.9 I got: llvm[0]: ***** Completed Debug Build llvm[0]: ***** Note: Debug build can be 10 times slower than an llvm[0]: ***** optimized build. Use make

Hi Joey! Thanks I just replied your message on stack and I was actually looking into this right now. Is this the option? I just wanted to confirm: - make [-j] - The -j specifies the number of jobs (commands) to run simultaneously. This builds both LLVM and Clang for Debug+Asserts mode. The --enabled-optimized configure option is used to specify a Release build. The -j parameter is

Hi, The -j option just says how many processes are started to parallelise the build. The default option is to build Debug+Asserts, so unless you add any extra arguments when you run './configure', you should be fine! Joey On 9 June 2012 21:29, Carlos Andrade <carlosviansi at gmail.com> wrote: > Hi Joey! > > Thanks I just replied your message on stack and I was actually

Hi Alex, Would you recommend any specific link in respect on how to compile in debug mode? I downloaded the Mac OS version on the website so I did not compile anything. I am sort of a rookie on bash but I should be able to figure my way around this. Also, is there any particular reason why this functionality is only available on debug mode? Thank you so much for the fast reply, was driving me

Hi Carlos, You can just download the source code from http://llvm.org/releases/download.html#2.9 and then read http://llvm.org/docs/GettingStarted.html which should tell you how to compile it. Joey On 9 June 2012 21:10, Carlos Andrade <carlosviansi at gmail.com> wrote: > Hi Alex, > > Would you recommend any specific link in respect on how to compile in > debug mode? I

I'm going to implement AdaBoost algorithm in R. Just wanted to ensure that there is no implementation of any boosting algorithm in R... don't want to reinvent the wheel... -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Dear all, I'm using adaBoost from the ada package to build a classification model. After training the model in R I'd like to use it in a Python application. Is it possible to export the model in some way to make translating into python easier? Any help would be greatly appreciated. Thanks. Bob

Dears, I am new to this list, and hope this question is pertinent to this mailing list. I have been trying to use Clang to extract an AST from my source code, but without success when attempting to do so with Graphviz. I created a thread on Stackoverflow recently in hope any could help me [1], but the question is actually pretty simple. I keep getting Stmt::viewAST is only available in debug

Hi Carlos, > I am new to this list, and hope this question is pertinent to this mailing > list. Welcome! > Stmt::viewAST is only available in debug builds on systems with Graphviz or > gv! You need to actually build Clang in debug mode for this particular method to be available, which is very likely why you're seeing this error. I don't think that Clang builds shipped with

I'm using Ubuntu 8.10 (Intrepid Ibex) and R 2.7.1. I've built a package from source (a modified version of gbm) and it contains some C++ code. I now want to cross-compile it to get a Windows version. I installed R using sudo apt-get update sudo apt-get install r-base sudo apt-get install r-base-dev So far as I can tell, I've also followed all the instructions in the guide

Hi, I'm looking to perform a classification analysis on an imbalanced data set using random Forest and I'd like to reproduce the weighted random forest analysis proposed in the Chen, Liaw & Breiman paper "Using Random Forest to Learn Imbalanced Data"; can I use the R package randomForest to perform such analysis? What is the easiest way to accomplish this task? Thanks,

Dear R-Helper, I want to know, is there any function/package can handle adaboost more two classes? I know packages gbm and boost, but there are only for 2 classes (correct me if I mistake). Regards, Muhammad Subianto

Hello, I performed a boosting analisis with adabag package to obtain a classification tree with the following set of commands: Tesis.boost <- adaboost.M1(Captura~., data=Tesis2, mfinal=2) > arb<-Tesis.boost$tree[[1]] > post(arb, file ="") > post(arb, file ="",title= "Arbol 1") I would like to know the meanning of the numbers that appeared in the

Hi, all, When running > AB.fit=adaboost(ylearn, xlearn, xtest, presel=0) I got the following error: Error in `[[<-.data.frame`(`*tmp*`, preds, value = c(4L, 6L, 6L, 6L, 3L, : replacement has 186 rows, data has 62 The data structure is attached below: [1] "ylearn" [1] 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 [40] 1 1 1 1 1 1 1 0

Hi, I am trying to implement the Adaboost.M1. algorithm as described in "The Elements of Statistical Learning" p.301 I don't use Dtettling 's library "boost" because : - I don't understande the difference beetween Logitboost and L2boost - I 'd like to use larger trees than stumps. By using option weights set to (1/n, 1/n, ..., 1/n) in rpart or tree

dear list, i have a problem using the adaboost function from the package boost. running the example of leukemia works out very well, but so it does not on my own data. i always get the following 22 warnings: 1: cannot compute exact p-value with ties in: wilcox.test.default(x[which(y == 0)], x[which(y == 1)]) can anybody please help me with the meaning of this warning. thnak you stefan