similar to: Help interpreting libarary(nnet) script output..URGENT

Hello, As a result of running linear discriminant analysis, I need to be able to plot the resulting file. I am not sure what the best way to do this is. So far I have tried regular plot("insert_file_name_here") command but the error it gives me is Error in plot.new() : figure margins too large here is sample LDA code I am working with .... library(MASS) example <-

Hello, I am trying to impute data with the mi() function (mi package) and keep receiving an error message. When imputing the variable, "sex," the mi() function accesses the mi.categorical() function, which then accesses the nnet() function. I then receive the following error message (preceded by my code below): > imputed.england=mi(england.pre.imputed, n.iter=6, add.noise=FALSE)

Dear All, I am quite new to R and am having a problem trying to run a linear model with random effects/ a regression- with particular regard to my variable lengths being different and the models refusing to compute any further. The codes I have been using are as follows: vc<-read.table("P:\\R\\Testvcomp10.txt",header=T) >> attach(vc) > > family<-factor(family) >

Dearest all, Objective: I am now learning neural networks. I want to see how well can train an artificial neural network model to discriminate between the two files I am attaching with this message. http://r.789695.n4.nabble.com/file/n2240582/3dMaskDump.txt 3dMaskDump.txt http://r.789695.n4.nabble.com/file/n2240582/test_vowels.txt test_vowels.txt Question: when I am attempting to run

I am trying to use the mi package to impute data, but am running into problems with the functions it calls. For instance, I am trying to impute a categorical variable called "min.func." The mi() function calls the mi.categorical() function to deal with this variable, which in turn calls the nnet.default() function, and passes it a fixed parameter MaxNWts=1500. However, as

Saludo gente, antes que nada gracias por la ayuda que puedan aportarme, soy iniciante en R, estoy usando el paquete Mice para realizar imputaciones múltiples sobre variables en su mayoría categóricas. El problema está que cuando expresó este comando imp <- mice(dataset,method="polr",maxit=1) donde el dataset es un data.frame me tirá este error : iter imp variable 1 1 pial1a

Hi, I'm trying to impute a large data set using mice but I keep getting this: Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE, softmax = TRUE, : too many (2944) weights nnet.default uses the argument MaxNWts to set a maximum number of weights. I've tried to change nnet.default to get around this, but mice is somehow still passing an argument that sets the maximum

Saludo gente, antes que nada gracias por la ayuda que puedan aportarme, soy iniciante en R, estoy usando el paquete Mice para realizar imputaciones múltiples sobre variables en su mayoría categóricas. El problema está que cuando expresó este comando imp <- mice(dataset,method="polr",maxit=1) donde el dataset es un data.frame me tirá este error : iter imp variable 1 1 pial1a

Dear all, I have found some difference of the results between multinom() function in R and multinomial logistic regression in SPSS software. The input data, model and parameters are below: choles <- c(94, 158, 133, 164, 162, 182, 140, 157, 146, 182); sbp <- c(105, 121, 128, 149, 132, 103, 97, 128, 114, 129); case <- c(1, 3, 3, 2, 1, 2, 3, 1, 2, 2); result <- multinom(case ~ choles

Hi, I'm using the R nnet package to train a classifier to recognise items which belong to a particular class and those which don't belong to the class. I'm supplying nnet with a matrix x containing training examples (in each row) and a matrix y of targets. The training set is made up of 200 positive examples and 1000 negative examples. I want to train the network on the same

Hello All, I am working with samr and nnet packages. I am following the steps given below: 1> I take a input file with signal values for 9506 genes and 36 chips , belonging to two classes. 2> I perform samr analysis on 80% of chip data from both the classes.(selected by random sampling) 3> I then use the data of only the significant genes from this samr analysis to train nnet. 4>

Dear R people, I am using tune.nnet from e1071 package to tune the parameters for nnet. I am using the following syntax: tuneclass <-c(rep(1,46),rep(2,15)) tunennet <-tune.nnet(x=traindata,y=tuneclass,size=c(50,75,100),decay=c(0,0.005,0.010),MaxNWts = 20000) Here traindata is the training data that I want to tune for nnet which is a matrix with 61 rows(samples) and 200

Hello all, I have searched and have not yet identified a solution so now I am sending this message. In short, I need to split my data into training, validation, and testing subsets that keep all observations from the same sites together ? preferably as part of a cross validation procedure. Now for the longer version. And I must confess that although my R skills are improving, they are not so

Hello, For a reason I can't seem to figure out (have searched posts on this forum for "filled.contour grid"), the grid (in the code below) is plotting over the legend that accompanies the filled.contour. The dataset has 40 columns and 20 rows. Where have I gone wrong? How can I draw a grid with 40 columns and 20 rows that is constrained to the plotted region and doesn't draw

Amalia, No obtengo tus resultados. Corrí tus formulas y datos y el resultado es x <- structure(list(ï..psraid = c(202517L, 202518L, 202520L, 202523L, + 202527L, 202537L, 202543L, 202544L, 202551L, 202566L, 202570L, + 202571L, 202606L, 202619L, 202624L, 202629L, 202631L, 202632L, + 202633L, 202648L, 202657L, 202663L, 202676L, 202683L, 202685L, + 202706L, 202708L, 202709L, 202710L, 202734L,

Saludo gente, antes que nada gracias por la ayuda que puedan aportarme, soy iniciante en R, estoy usando el paquete Mice para realizar imputaciones múltiples sobre variables en su mayoría categóricas. El problema está que cuando expresó este comando imp <- mice(dataset,method="polr",maxit=1) donde el dataset es un data.frame me tirá este error : iter imp variable 1 1 pial1a

I''m starting to play with the tooltip.js library from http://tooltip.crtx.org/index.php?page=HomePage. The libarary seems to work pretty well except that when I use a tooltip on a web page that has a form and submit buttons, the submit buttons stop functioning and won''t respond to click events anylonger. So far I''ve only been able to reproduce this under Safari.

Hi Guys, I''ve got a rails application that uses activeldap to authenticate users. Its been working great for about 6 months now, but a user from mexico started using it recently, but can''t seem to login. I''ve narrowed it down to the fact that his password contains a ñ character in it. This problem is also present in a test user account I''ve setup. ActiveLDAP

Muchas gracias, pero claro en una muestra de 50 datos se ejecuta, en la muestra original de 1000 registros me tira error :( 2013/10/30 daniel <daniel319@gmail.com> > Amalia, > > No obtengo tus resultados. Corrí tus formulas y datos y el resultado es > x <- structure(list(ï..psraid = c(202517L, 202518L, 202520L, 202523L, > + 202527L, 202537L, 202543L, 202544L, 202551L,

Hi I am not able to have a working tcltk library in R-2.2.1 inspite of trying different options suggested in the FAQ's. I am using the following configure option and I do get the tcltk package installed but with a missing libs folder. ./configure -prefix= "~R-2.2.1" --enable-R-shlib --enable-linux-lfs --with-zlib --with-gnu-ld --with-tcltk