similar to: Doubt about adaboost

Hello, I would like to know how to obtain the misclassification error when performing a boosting analisis with ADABAG package? With: > prop.table(Tesis.boostcv$confusion) I obtain the confusion matrix, but not the overall missclassification error. Thanks in advance, BSc. Cecilia Lezama Facultad de Ciencias - UDELAR Montevideo - Uruguay. [[alternative HTML version deleted]]

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

Hello, I'm trying to use adabag to make bagging and boosting with bagging() and adabost.M1(), respectively, but in both cases it produces an abnormal termination of R. My code is: bagging(I.NOSOCO~EDAD+SEXO+ESTANCIA+ADMISI?N+T.CIRUG?+DURACI?N+CONTAMIN +PROFILAX+E.PREOPE+V.PERIFE+V.CENTRA+S.VESICA+S.NASOGA+DREN.ABI+DREN.CER

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

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 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

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

Ok, so basically I have a dataframe named data_frame data_frame contains: startdate startprice endpricethreshold1 endpricethreshold2 endpricethreshold3 all of these endpricethresholds are true/false binary vectors. They are true or false depending on whether the endprice was above or below whatever the endpricethreshold is. now I want to try to use lets say the general linear model to have

OK, Thanks a lot Karl and Elf. It's clear to me now. Shoutcast gives you (by default) a much larger burst and that's the difference I was seeing. By the way: do you know sources for lists of stations? I see a "stream directory" at icecast.org, but I don't know if it's available to download (I think using a program to dig the info from the web is not ethical, as least

Hi, I want to connect as a client. Please let me know about the listings you mention. I?ve just asked this on another thread in the dev list: I see a "stream directory" at icecast.org, but I don't know if it's available to download (I think using a program to dig the info from the web is not ethical, as least without permission). Shoutcast has a nice directory but

http://bugzilla.netfilter.org/show_bug.cgi?id=586 Summary: Problems changing the source address of a packet Product: libnetfilter_queue Version: unspecified Platform: All OS/Version: All Status: NEW Severity: blocker Priority: P1 Component: libnetfilter_queue AssignedTo: laforge at netfilter.org

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]]

my problem can be explained with the following example: x <- 1:12 y <- 13:24 a <- data.frame(x = x, y = y) ## if i write a$x ## it returns [1] 1 2 3 4 5 6 7 8 9 10 11 12 ## but the function get doesn't recognize a$x. Instead it produces the following error: get("a$x") Error in get(x, envir, mode, inherits) : variable "a$x" was not found i intend to do

Dear R-helpers, I am looking for a segmentation package that gives some "tree identifier" as output for every observation in the data set (my response variable is binary). I have skimmed through "rpart", "ada" and "adabag": The output "trees" gives you the formula, but I have to run several thousand segmentations on different data sets and it

Hello! Does anyone know how to apply bagging for SVM? ( for example) I am using adabag package to execute bagging but this method, "bagging", works with classification trees. I would like to apply my bagging to other classifiers as SVM,RNA or KNN. Has anyone do it? Thanks!! [[alternative HTML version deleted]]

Hello all, I using lmer to develop a mixed effects model. I start with an overly parameterized model (as suggested in Zuur et al. Mixed Effects Models and Extension in Ecology with R) that looks something like this: m1 <- lmer( Y ~ aS + bS + c + d + e + (c|SpeciesId) + (d|SpeciesId) + (e|SpeciesId)) aS and bS are species level predictors an so do not vary within a SpeciesId. However, c, d, and

Hi, I have all CRAN packages installed on my Linux. Now I have problems with JGR. When I make a plot and close a device, the device dont work anymore, I nedd to use before javaGD() and after plot(). When I try do close JGR and save a session, It return a erro and dont close. Look: Exception in thread "Thread-2" java.lang.IllegalArgumentException: Value too long:

Dear R-users,   I am trying to run a function of the package “adabag” (e.g. boosting.cv) in order to determine a proper number of cluster that I would specify later on my KMeans clustering. (I had this idea from: http://www.statsoft.com/TEXTBOOK/stcluan.html)   However, I do have a problem with the “formula” parameter of e.g. boosting.cv : I am not familiar with these formulas and my

Buenas, Estoy creando unos modelos donde necesito normalizar los datos antes de crear el modelo. Estoy haciendo árboles de clasifciacion, pero me surge la duda de saber como tengo que hacer, pues cuando muestro el arbol me sale con lo svalores normalizados, pero me gustaria uqe el arbol diera ya directamente las conclusiones con los datos no normalizados. Lo que hago yo ahora es desnormalizar