similar to: SOM (Self-organizing map)

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.

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

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'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, 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

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 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

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

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:

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

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]]

I am writing bindings to the C library (neural network simulator SNNS). DLL was produced with the command R CMD SHLIB [source with C-wrappers, callable from R with .C and all sources from the snns kernel] I used latest MinGW. The problem is. R crashes with the "segmentation violation". Tracing with the insight and with simple Rprintf's gave me that crash occurs on the call of the

Hi, > > I think one idea to improve the situation is to consider the cost vector of adjacent nodes during RN. Let's say you decided to do a RN for node A and want to compute the costs for choosing register %Ri. The current implementation does this by computing min(row/column i of edge A <--> B) but you can do better by adding B's cost vector to the row/column before computing

> (1) Spill cost metrics. I think this one cannot be dissociated from some kind of live range pre-splitting. Cheers, Arnaud From: Lang Hames [mailto:lhames at gmail.com] Sent: 03 June 2016 23:15 To: James Molloy Cc: Arnaud De Grandmaison; llvm-dev at lists.llvm.org; Sebastian Buchwald; Bernhard Scholz Subject: Re: [llvm-dev] PBQP register allocation and copy propagation Hi James, Arnaud,

I've put all ``current'' add-on packages into CRAN's source/contrib tree and created an INDEX file (attached below). As you can see, currently we have acepack bootstrap ctest date e1071 fracdiff gee jpn snns splines survival4 (Yes, e1071 and jpn are new ... more on the latter in a later mail.) In the near future, I am hoping for the following: oz (Bill

Hi everyone, I'm a graduate student of engineering, lately introduced with R. and using R for my project and thesis. I'm trying to use R for implementing a neural network regression model and apply it to my database. I found three R packages ("AMORE" , "grnnR" , "neural") in R website, but their manuals are not really user-friendly in my idea. I was wondering

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 use SOM package to cluster some gene expression data. I got stuck with 2 questions and can't not find any documents to resolve these matters. I would really appreciate if anybody can shed some sort of light. Q1. I clustered the data using SOM function and plotted it using plot function. But I can't figure out how I can list the data elements belongs to different clusters. I

I want to create a neural network, and then everytime it receives new data, instead of creating a new nnet, i want to use a backpropagation algorithm to adjust the weights in the already created nn. I'm using nnet package, I know that nn$wts gives the weights, but I cant find out which weights belong to which conections so I could implement the backpropagation algorithm myself. But if anyone