similar to: predict.kohonen for SOM returns NA?

I have a data set with 10 variables, and about 8000 instances (or objects/rows/samples). In addition I have one more ('class') variable that I have about 10 instances for, but for which I wish to impute values for. I am a little confused how to go about doing this, mostly as I'm not well-versed in it. Do I train the SOM with a data object that contains just the first 10 variables

Hi All, I am still learning R, but making, IMO, great strides. I learned about Kohonen/Self-Organizing Maps in class and I would like to try to replicate some of the things we have seen in class. Below is my code. I am trying to create a u-matrix. In the documentation on page 9 it appears the type of plot, dist.neighbours should do the trick, however, I am getting an error: (Error in

Hi, I have a question about using lm on matrix, have to admit it is very trivial but I just couldn't find the answer after searched the mailing list and other online tutorial. It would be great if you could help. I have a matrix "trainx" of 492(rows) by 220(columns) that is my x, and trainy is 492 by 1. Also, I have the newdata testx which is 240 (rows) by 220 (columns). Here is

Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...) however I don't know how to build trianx and trainy for my data set, and I could not understand the way trainx is built in the package

Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...) however I don't know how to build trianx and trainy for my data set, and I could not understand the way trainx is built in the package

Any responds?! On Wednesday, August 23, 2017 5:50 AM, Elahe chalabi via R-help <r-help at r-project.org> wrote: Hi all, I would like to do cross validation in random forest using rfcv function. As the documentation for this package says: rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...) however I

I would really like some or any advice on how I can improve (or fix??) the following analysis. I hope I have provided a completely runnable code - it doesn't produce any errors for me. The resulting plot at the end shows a pretty poor correlation (just speaking visually here) to the test set. How can I improve the performance of the mapping and prediction? Here are some of the data

Hi, I'm trying to utilize the kohonen package to build SOM's. However, trying this on my data I get the error: "Argument data should be numeric" when running the som(data.train, grid = somgrid(6, 6, "hexagonal")) function. As you see, there is a problem with the data type of data.train which is a list. When I try to convert it to "numeric" I get the error:

Hi all, I used the following code and data to get auc values for two sets of predictions: library(caret) > table(predicted1, trainy) trainy hard soft 1 27 0 2 11 99 > aucRoc(roc(predicted1, trainy)) [1] 0.5 > table(predicted2, trainy) trainy hard soft 1 27 2 2 11 97 > aucRoc(roc(predicted2, trainy)) [1] 0.8451621 predicted1: 1 1 2

HI, Dear R community, I am using the following codes to do the som. I tried to label the notes by the majority vote. either through mapping or prediction. I attached my output, the left one dont have any labels in the note, the right one has more than one label in each note. I need to have only one label for each note either by majority vote or prediction. Can anyone give some suggestions or

Sir, This query is related to randomForest regression using R. I have a dataset called qsar.arff which I use as my training set and then I run the following function - rf=randomForest(x=train,y=trainy,xtest=train,ytest=trainy,ntree=500) where train is a matrix of predictors without the column to be predicted(the target column), trainy is the target column.I feed the same data

Hi All, I am experimenting with using binary data (1, 0) in the kohonen package. I would like either 1 or 0 to be mapped in SOM, but the package gives me 1 or 0 (as expected), but something in between. I am not scaling the binary data, but still there are in-between values. Can anybody suggest a way to keep the data binary, even in the SOM plot? Thanks a lot. George

I am learning the package "caret", after I do the "rfe" function, I get the error ,as follows: Error in `[.data.frame`(x, , retained, drop = FALSE) : undefined columns selected In addition: Warning message: In predict.lm(object, x) : prediction from a rank-deficient fit may be misleading I try to that manual example, that is good, my data is wrong. I do not know what

Hola, alguien me puede decir cómo descargar la librería "kohonen", pues lo he intentado con download.packages y no hay forma. No sé si es porque pongo mal el directorio de destino o porque esa librería esta dentro de otra y no la localizo. Ya he usado en otras ocasiones el comando download.packages y no me había dado problemas gracias [[alternative HTML version deleted]]

Does anyone know of any SOM library for R? or any stand alone freeware? A search from google returns SOM_PAK 3.1 developed at Helsinki University of Technology. Is there newer version? Jun -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Hi. Three years ago, I've read the question of availability of SOM library for R using Kohonen's SOM_PAK in this mailing-list. This answer was no availability. And no package dealing with SOM in CRAN. Is this situation same? Could you tell me availability this library? Best Regards.

Hi All, I'm looking for some reference paper about SOM (self organizing map) algorithm. I tried the paper which is mentioned in the help page of function "som (package:som)": http://www.cis.hut.fi/research/papers/som_tr96.ps.Z But I can't open it for some reason. Could you please help me with it ? Thanks a lot! [[alternative HTML version deleted]]

Hi, I am trying to construct a svmpoly model using the "caret" package (please see code below). Using the same data, without changing any setting, I am just changing the seed value. Sometimes it constructs the model successfully, and sometimes I get an ?Error in indexes[[j]] : subscript out of bounds?. For example when I set seed to 357 following code produced result only for 8

This was sent to me personally but was probably meant for R-help. -------- Original Message -------- Subject: Re: [R] Kohonen Package Date: Mon, 1 Mar 2010 14:45:13 +1000 From: Martin <labadz at gmail.com> To: ehlers at ucalgary.ca Hi Any idea if the kohonen package can produce umatrices with hexagons and component planes as found in various publications? Cheers Martin Martin Labadz

hi all, i would like to apply the kohonen 's algorithm (SOM). Somebody knows if there is an available script ? thanks -- ------- Olivier MARTIN -------- _______________________________ _______________________________ CEA 17, rues des martyrs LETI/DSYS/SCSI Bur 225 olivier.martin at cea.fr 04 76 88 47 61 (bur.) 04 76 88 57 87 (fax.) ---------------------- 06 08 67 93 42 (pers.)