similar to: randomForest: How to append ID column along with predictions

Hi I am new to R, randomForest and I have read about how to use it in your old mails. I have also run the predictions examples from CRAN. But I still don't understand how to use it right. The thing that I don't understand is how to run the result from the randomForest on one line (post) with newdata to get a good guess. What I mean is if I put in a new observation of iris how do I

Hello, I am new and am having a hard time getting the proper syntax for output from loops. I am working on a simulation to generate a null expectation of bee behavior. Pieces of it work. The part that I am having specific difficulty is in output of a vector from within the while loop that I am using. Basically the simulation works as such: I have a starting point and a neighbor matrix and a

Hi all, I am trying to set up a simple path analysis in the SEM package, but I am having some trouble. I keep getting the following error message or something similar with my model, and I'm not sure what I'm doing wrong: Error in solve.default(C) : system is computationally singular: reciprocal condition number = 2.2449e-20 In addition: Warning message: In sem.default(ram = ram, S = S,

Dear list, I came across the following error for three of my newly written Rd-files: non-ASCII input and no declared encoding I can't make sense of this. Below I copied in one of the three files. Can anybody please tell me what's wrong with it? Thank you, Christian \name{tetragonula} \alias{tetragonula} \alias{tetragonula.coord} \docType{data} % \non_function{} \title{Microsatellite

Dear all, I'm discovering the somehow confusing (for me) world of linear mixed models after having been advised it could be the best option to analyze my dataset. After several days of reading, I'm not sure that what I ended up with makes some sense and I'd greatly appreciate any help and explanations. The dataset has been obtained as follows. In 15 different locations, I counted

Hi there, Here is my situation: > User NEWBIE!!!!! > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.2 year 2001 month 02 day 26 language R I wonder why. Given this data

Hello, I am still a newbie to Linux, but I can find my ways around as long as I have help. For some reason if I leave my iptables enabled, I will lose my Samba share connection after a few minutes. Of course, then iptables disabled, I have no problems. I am using Debian with Kernel 2.6.14-K7. Is this normal? Thank you in advance. :) -- "Ever watch ants just crawling around? They walk in

Hi all, I have a dataset consisting of 5 columns and over 5000 rows. Each row gives information about an individual animal, including longevity, i.e. at what age an animal died. For the model I use I need to create n rows for each animal, n being its longevity, and a new column 'survival' with a binary 0/1 outcome. When an animal died e.g. at age 5, there have to be 5 rows of identical

I've built two RF objects (RF1 and RF2) and have tried to combine them, but I get the following error: Error in rf$votes + ifelse(is.na(rflist[[i]]$votes), 0, rflist[[i]]$votes) : non-conformable arrays In addition: Warning message: In rf$oob.times + rflist[[i]]$oob.times : longer object length is not a multiple of shorter object length Both RF models use the same variables, although

Hello, I am working on my thesis and can't really figure out how to produce a reasonable graph from the output from my glm., I could just give the R-output in my results and then discuss them, but it would be more interesting if I could visualise what is going on. My research is how bees react to different fieldmargins, for this I have 4 different types of field margin (A,B,C & D) and

I have a question on the output generated by randomForest in classification mode, specifically, the confusion matrix. The confusion matrix lists the various classes and how the forest classified each one, plus the classification error. Are these numbers essentially averages over all the trees in the forest? If so, is there a way I can get the standard deviation values out of the randomForest,

Hi all, I am trying to predict a target variable that takes values 0 or 1 using the rpart command. In my initial dataset I have few positive observations of the target variable; therefore I have oversampled the rare event by a multiple of 6 (i.e. from 762 to 4572). However, in my results, I end up with a number of positives in one of the terminal nodes that is not divisible by 6. As I have the

Hi have been trying to get winbind working on Solaris 9 but to no effect. version info: samba: 3.0.0 openldap: 2.1.23 kerberos: MIT 1.3.1 Have followed the instructions in every howto, usenet posting I could find: nscd not running created relevant links in /lib and /lib/security/sparcv9 applied patch for nsswitch as recommended kinit -e works net ads join works wbinfo -t works wbinfo -u

I am after a nice way to disable (not destroy, delete nor nullify) all associated records. I''m a hoarder, I don''t want to get rid of anything but I want to stop records being visible. I have a disabled boolean in my tables and if I disable the top record in the association (say the association is 5-6 levels deep), I would like to cleanly disable its children. I''ve

RF trains fine with X, but fails on prediction > library(randomForest) > chirps <- c(20,16.0,19.8,18.4,17.1,15.5,14.7,17.1,15.4,16.2,15,17.2,16,17,14.1) > temp <- c(88.6,71.6,93.3,84.3,80.6,75.2,69.7,82,69.4,83.3,78.6,82.6,80.6,83.5,76 .3) > X <- cbind(1,chirps) > rf <- randomForest(X, temp) > yp <- predict(rf, X) Error in predict.randomForest(rf, X) : subscript

I would like to ask a general question about the randomForest predict function and how it handles No Data values. I understand that you can omit No Data values while developing the randomForest object, but how does it handle No Data in the prediction phase? I would like the output to be NA if any (not just all) of the input data have an NA value. It is not clear to me if this is the default or

Dear R-users, While making a prediction using the randomForest function (package randomForest) I'm getting the following error message: "Error in predict.randomForest(model, newdata = CV) : No forest component in the object" Here's my complete code. For reproducing this task, please find my 2 data sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).

[R-0.50-a3] It seems intuitive that attach( .., pos = 1) is harder than other attach()es. But still... If it ever will work, it is even more important to have detach( .... , save = "VAR.name") ~~~~~~~ -------- to be working. The documentation says that detach(.) returns invisibly. Therefore, we don't NEED the above 'save = ' argument to detach, since we can

Dear R-experts, Here below a toy example with some error messages, especially at the end of the code (Tuning the parameters). Your help to correct my R code would be highly appreciated. ####################################### #libraries library(lattice) library(ggplot2) library(caret) library(randomForest) ?? #Data

I've been training randomForest models on 7 million rows of data (41 features). Here's an example call: myModel <- randomForest(RESPONSE~., data=mydata, ntree=50, maxnodes=30) I thought surely with only 50 trees and 30 terminal nodes that the memory footprint of "myModel" would be small. But it's 65 megs in a dump file. The object seems to be holding all sorts of