similar to: SOS Boosting

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

Everyone, I've got code in my package that uses LogitBoost from the caTools package. caTools does not have a namespace. My package also uses loads RWeka, which has a namespace, and also has a function called LogitBoost. After loading both packages, how can I be specific about running the version from caTools (since caTools:::LogitBoost won't work)? Thanks, Max

Hello, does any one know how to interpret this output in R? > Classification with logitboost > fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20) > summarize(fit, ytest) Minimal mcr: 0 achieved after 6 boosting step(s) Fixed mcr: 0 achieved after 20 boosting step(s) What is "mcr" mean? Thanks [[alternative HTML version deleted]]

When I sink the output of an RWeka model to a text file, the output file appears empty: library(RWeka) model = LogitBoost(Species~.,data=iris) print(model) sink("output.txt") print(model) #file output.txt is created, but it is blank sink() Am I doing anything wrong? [[alternative HTML version deleted]]

Hi I am using boosting for a classification and prediction problem. For some reason it is giving me an outcome that doesn't fall between 0 and 1 for the predictions. I have tried type="response" but it made no difference. Can anyone see what I am doing wrong? Screen output shown below: > boost.model <- gbm(as.factor(train$simNuance) ~ ., # formula +

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

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

Hi, I have been searching everywhere for an implementation of those algorithms, but I have only observed them in Matlab and on the literature. I noticed a package called 'ada' in CRAN but it is not for multi class. I would be happy with just Adaboost.m2, Smoteboost over adaboost.m2 or any other combination that could account for imbalanced multiclass classification problems. Thanks!

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

You are right, maintainer does keep a list of model's packages. So how do I use a variable instead of $adaboost$? getModelInfo()$adaboost$library Also, server not found: http://rwiki.sciviews.org/doku.php?id=getting-started:reference-cards:getting-help On Tue, Aug 1, 2017 at 11:46 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > I have provided you all the

Hi, and sorry for asking such an unspecific question. Does anybody know of statistical / data mining methods that are available in R that are not in SAS ? With SAS I mean the SAS System Version 9.4 and SAS Enterprise Miner. I don't expect a complete list, just two or three examples or hints where and what to look for. I found some older comparisons, and the R methods mentioned there

You should read the section on Indexing in the Introduction to R document that comes with R, regarding $ and `[[`. -- Sent from my phone. Please excuse my brevity. On August 1, 2017 2:44:18 AM PDT, Dimlak Gorkehgz <rain8dome9 at gmail.com> wrote: >You are right, maintainer does keep a list of model's packages. > >So how do I use a variable instead of $adaboost$? >

Working on the caret package has exposed me to the wide variety of approaches that different authors have taken to creating predictive modeling functions (aka machine learning)(aka pattern recognition). I suspect that many package authors are neophyte R users and are stumbling through the process of writing their first R package (or R code). As such, they may not have been exposed to some of the

Hi all; Happy new year. I have got the following error rror in if (nrow(object$splits) > 0) { : argument is of length zero when I am running the following codes. train <- c(sample(1:27,18), sample(28:54, 18), sample(55:81, 8)) a2011.adaboost <- boosting(median_kod ~ ., data = b[train, ], boos=TRUE, mfinal = 10, control = rpart.control(minsplit = 0)) Regards, Greg [[alternative

Dear Developers, I am a data science student. I wish to implement Neuro fuzzy Classifier, Adaboost, MLkNN Multi label algorithms for web document classification. I could not find packages and steps for above mention algorithms in mlr <https://mlr-org.github.io/mlr-tutorial/devel/html/multilabel/index.html>. Hence i request you to give your valuable suggestions. In need of your guidance,

HI, Guys, I am trying to use the AdaBoosting. M.1 algorithm to integrate three models. I found the sum of weights for each model is not equal to one. How to deal with this? Thanks, any response or suggestions are appreciated! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

Full_Name: The Manager Version: 2.0.1 OS: Solaris 9 Submission from: (NULL) (129.67.80.243) > install.packages("gbm") trying URL `http://cran.uk.r-project.org/src/contrib/PACKAGES' Content type `text/plain; charset=ISO-8859-1' length 52975 bytes opened URL ================================================== downloaded 51Kb trying URL

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

Hi All, I am trying to use the C50 package to build classification trees in R. Unfortunately there is not enought documentation around its use. Can anyone explain to me - how to prune the decision trees? Regards, Indrajit [[alternative HTML version deleted]]

> On Aug 14, 2017, at 12:22 PM, fs <mail at friedrich-schuster.de> wrote: > > Hi, and sorry for asking such an unspecific question. > > Does anybody know of statistical / data mining methods that are available in R > that are not in SAS ? With SAS I mean the SAS System Version 9.4 and SAS > Enterprise Miner. I don't expect a complete list, just two or three