similar to: gbm for multi-class problems

Dear List, I´m trying to implement the functionalities from WEKA into my modeling project in R through the RWeka package. In this context I have a slightly special question about the filters implemented in WEKA. I want to convert nominal attributes with k values into k binary attributes through the NominalToBinary filter ("weka.filters.supervised.attribute.NominalToBinary"). But

Hi list, I´m working on a predictive modeling task using the caret package. I found the best model parameters using the train() and trainControl() command. Now I want to evaluate my model and make predictions on a test dataset. I tried to follow the instructions in the manual and the vignettes but unfortunately I´m getting an error message I can`t figure out. Here is my code: rfControl <-

Hello List, I`m trying to make prediction using a bagged tree with the package ipred. I tried to follow the manual but I`m getting an error message. Also browsing through the list-archive I didn`t find any hint. Maybe someone can help me? selbag <- bagging(SOIL_UNIT ~., data=traindat.bin, coob=TRUE) Error in dimnames(X) <- list(dn[[1L]], unlist(collabs, use.names = FALSE)) :

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order to

Hello, I want to draw 3D cylinder objects in R. Given is the length and the diameter of the cylinder. Has anybody an example? Thank you very much! Best regards -- ---------------------- Dr. Hans-Joachim Klemmt Forstoberrat Organisationsprogrammierer IHK Bayerische Landesanstalt f?r Wald und Forstwirtschaft zugewiesen an Lehrstuhl f?r Waldwachstumskunde Technische Universit?t M?nchen

The data frame is lwf that records the survival of bushes over an 8 year period. Years are called bouts. Dead bushes are recorded as zeros, and live bushes as "1." str(lwf) 'data.frame': 638 obs. of 9 variables: $ bushno: int 1 2 3 4 5 6 7 8 9 10 ... $ bout1 : int 0 1 0 1 1 1 0 1 0 1 ... $ bout2 : int 0 1 0 0 0 0 0 0 0 1 ... $ bout3 : int 0 1 0 0 0 0 0 0 0 1 ... $

Hi, under the new version R 2.7.1 I can't use WinEdt. It seems that there is a bug in that version. To use older versions of the package RWinEdt doens't bring success. The Use of R 2.7.0 doesn't cause that Problem. Regards, Hans-J?rgen Auinger -- ---------------------------------------------- Hans-J?rgen Auinger Lehrstuhl f?r Pflanzenz?chtung Wissenschaftszentrum Weihenstephan

On page 409 of "Applied Predictive Modeling" by Max Kuhn, it states that the gbm function can accomodate only two class problems when referring to the distribution parameter. >From gbm help re: the distribution parameter: Currently available options are "gaussian" (squared error), "laplace" (absolute loss), "tdist" (t-distribution

Generalized Boosted Models (gbm) This package implements extensions to Y. Freund and R. Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine (aka multivariate adaptive regression trees, MART). It includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards/partial likelihood, and the AdaBoost exponential loss. It handles

Generalized Boosted Models (gbm) This package implements extensions to Y. Freund and R. Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine (aka multivariate adaptive regression trees, MART). It includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards/partial likelihood, and the AdaBoost exponential loss. It handles

Hi All, I am considering testing out some analog sets with * for a customer and thought I would ask what analog phones are in use? The customer would require the usual business functionality ie hold, conference calling, and preferably a soft key to vm and line apearances(correct terminology?) in order for secretary to see if their boss is on the phone before transferring a call, etc. I would

Hi all, I'm currently trying to bootstrap llvm-gcc-4.2 from the latest stable LLVM release 2.6 on Solaris SPARC. The compilation with a self-build gcc-4.2.4 goes pretty well, however, I hit a seemingly widely know error during llvm-gcc's bootstrap in getting an assertion during the compile of /data/LLVM/src/GCC/RELEASE_26/gcc/libgcc2.c: /data/LLVM/src/GCC/RELEASE_26/gcc/libgcc2.c: In

Hello *, i have some problems to compile/configure OpenSSH on SunOS 5.5.1 with AFS. See the attachment for the compile environment. The programs compile fine and token passing is without problems. Unfortunately it is not possible to login without a valid token (`Permission denied.'). There is following message in the syslog: Kerberos v4 TGT for ... unverifiable: Principal unknown

Hi folks, i?m not sure if it is even possible, bu just want to ask: I have to servers connected over vpn. On both sides there is a working directory "Office" where the users are working on but deletion should only be possible on side A. The idea is, that on A and B people can work and save over their 100 Mbit Network quite fast, and in the backround the data get synchronized over

Hi Anton, thanks for the fast response. Ty->dump() prints "{double, double}" in the failing case (just before my introduced assert). HTH, and regards, Juergen On 10/30/09 16:19, Anton Korobeynikov wrote: > Hello, Juergen > >> With the full patch, I get the assertion of the 'unhandled REAL_TYPE!', >> so I wonder what needs to be done in order to get

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On Thu, 6 Feb 2014, Phil wrote: > Im new to postfix-dovecot and Unix/Linux, too? > and im mystified by the following results in ubuntu > 10.04lts > > :~$ dovecot -n > # 1.2.9: /etc/dovecot/dovecot.conf > Error: ssl_key_file: Can't use /etc/ssl/private/ssl-mail.key: Permission > denied >

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Hi, there: I am always experiencing the scalability of some R packages. This time, I am trying gbm to do adaboosting on my project. Initially I tried to grow trees by using rpart on a dataset with 200 variables and 30,000 observations. Now, I am thinking if I can apply adaboosting on it. I am wondering if here is anyone who did a similar thing before and can provide some sample codes. Also any

I' ve seen that several people are looking for a function that creates a barplot with an error indicators (I was one of them myself). Maybe you will find the following code helpful (There are some examples how to use it at the end): # Creates a barplot. #bar.plot() needs a datavector for the height of bars and a error #indicator for the interval #many of the usual R parameters can be set:

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