similar to: SOM object manupulation

Hi all, I originally posted this to the bioconductor group, but maybe it's better suited to the r-help... I'm using som() to partition samples of gene expression data into clusters. The point is to classify control vs. experimental cases (sample clustering). The original matrix was 22283 x 8. The 8 samples have 4 controls and 4 experimentals. I transposed the matrix so that its dim

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, 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

All, The kohonen predict function is returning NA for SOM predictions regardless of data used... even the package example for a SOM using wine data is returning NA's Does anyone have a working example SOM. Also, what is the purpose of trainY, what would be the dependent data for an unsupervised SOM? As may be apparent to you by my questions, I am very new to kohonen maps and am very grateful

R version 2.9.2 (2009-08-24) - for windows > library(SOM) Error in library(SOM) : there is no package called 'SOM' Where can I get the SOM library from? Thanks in advance -- View this message in context: http://old.nabble.com/SOM-library---where-do-I-find-it-tp26415633p26415633.html Sent from the R help mailing list archive at Nabble.com.

I am trying to understand how the SOM algorithm works using library(class) SOM function. I have a 1000*10 matrix and I want to be able to summarize the different types of 10-element vectors. In my real world case it is likely that most of the 1000 values are of one kind the rest of other (this is an oversimplification). Say for example: InputA<-matrix(cos(1:10),nrow=900,ncol=10,byrow=TRUE)

Is there an implementation of the SOM ('Self Organizing Map') procedure in R ? I am aware of the implementations of Sammon mapping, multidimensional scaling and, somewhat peripherally, principal curves and projection pursuit .. but not SOM per se as far as I can see. Am I missing something? --------------------- for anyone interesed in SOM I found Samuel Kaski's thesis

Bug in "SOM" package in R. This simple code withot for loop runs:-------simple.r-------- library(som) A <- as.matrix(read.table("C:/code/h.txt", sep="\t", header=TRUE, row.names=1)) print(som(A,1,2)$visual) print(som(A,1,3)$visual) ---------------------------------------- The same code if inserted in for loop generates "Assertion failure" in

Hello everyone, I'm new to this list, so let me introduce myself: my name is Jonck van der Kogel and I am a graduate student at the Erasmus University of Rotterdam. I am currently working on my thesis which is on the use of artificial intelligence for large data-sets. To do an analysis of a certain data-set I want to use Kohonen's SOM algorithm. However, as I understand it, the SOM

Hi all, I have a question about the SOM routine. You can either supply the initial representatives for the lattice yourself or else they are chosen randomly from the dataset. Is it possible to pass the random-seed as an argument somehow, when choosing the random initialisation of the lattice? As it is now, each time I run a SOM on a dataset with the same settings the resulting SOM will still

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]]

The (slow) SOM code can be found on my web page (towards the bottom) http://peabody.vanderbilt.edu/depts/psych_and_hd/faculty/wallern/ On Thu, 1 Mar 2001, John Aitchison wrote: > > Is there an implementation of the SOM ('Self Organizing Map') procedure in > R ? > > I am aware of the implementations of Sammon mapping, multidimensional > scaling and, somewhat

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 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

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, 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 Martin, you seem to do a lot of work on CTDB. Let me ask a question... Is there a way to segment CTDB/Samba to minimize chatter? Specifically, what I have in mind... In recent years advances have been made in distributed SQL databases (ideas which are applicable here) whereby the communication profile between peers are minimized, and synchronization is never necessary except in circumstances

> first <- data.frame(a=1:3, b=4:6) > second <- data.frame(b=7:9, c=10:12) > third <- merge(first, second, by="b", all=TRUE) > third b a c 1 4 1 NA 2 5 2 NA 3 6 3 NA 4 7 NA 10 5 8 NA 11 6 9 NA 12 It's easy to replace the Nas with whatever value you want. No, merge() does not work with more than two data sets at a time. Andy From: mtb954 at gmail.com

In the name of Allah. hello, how are you? I sent a mail for you,yesterday but I didn't recieve to my aim. I need to some data frames in version 1.7.0 such as "florida","Barley","rainforest" and some others. I don't know these data frames are in which library. I typed "data(package = .packages(all.available = TRUE))" that was in "data()"

Me encuentro de vacaciones hasta el proximo 16/02. Por favor contactar a Pablo Minsteras (pablo.minsteras at utopixnetworks.com) o Gustavo Hernandez (gustavo.hernandez at utopixnetworks.com). Muchas Gracias, Gustavo Scheveloff