search for: kohonen

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...

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...

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 a...

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 PhD Reserach Student Queens...

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...

...ed 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 (exclude the 'class' variable), then predict using an object that has all of the variables (including the class variable)? (I am using the kohonen package, and in general I am using the SOM technique as a comparison to some other methods). I don't know if providing some or all data is useful, please let me know if you think it is. # get the data bw <- read.csv("bw.csv") # some missing values in data bwm <- data.frame(na....

...i/6068259 The first variable is the dependent. I wish to train a som using this data, and then be able to predict MEAS_TC using a new set of data with missing values of MEAS_TC. Below I'm simply splitting the somdata into a training and a testing set for evaluation purposes. # ===== # library(kohonen) somdata <- read.csv("somdata.csv") # Create test and training sets from data: inTrain <- sample(nrow(somdata), nrow(somdata)*(2/3)) training <- somdata[inTrain, ] testing <- somdata[-inTrain, ] # Supervised kohonen map, where the dependent variable is MEAS_TC. # Attempting...

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.)...

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. Geor...

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

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.

...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 algorithm as it's implemented in R only gives a visual representation of the topological mapping. I want to do further analysis with this mapping and thus I need to do a clustering of the topological mapping produced by the SOM. I wa...

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 everybody! I try to implements Self-Organizing Maps with R and the Kohonen package. I have made an algorithm that try differents width and height. For each step, Silhouette index, Davies-Bouldin index and Dunn index are computed. However, there is always after severals minutes a *Runtime error* appears on the window: Microsoft visual c++ runtime library "this applic...

Dear list, I am running R2.11.1 on 32 bit windows. I am receiving messages as follows ... > require(car) Loading required package: car Error: package 'car' was built before R 2.10.0: please re-install it The package kohonen was another example. This failure appears to be fatal and not only affects the package concerned, but also all its dependents. Is there anything I can do at my end, or do I have to wait for the packages to be re-built, Thanks, Philip This message should be regarded as confidential. If you hav...

Dear R helpers I'm experimenting with the 'kohonen' package and have two questions. I've been following examples in the package manual and the paper from the Journal of Geostatistical software (October 2007, Volume 21, Issue 5.). I've set up a file with the 'animals' data (see attached file) which I used test a SOM routine I...

...e? Thanks so much! alex<-read.table("/home/cdu/operon/alex2.txt", , sep="\t", skip=0, header=T, fill=T) alex1<-alex[,c(1:257)] levels(alex1$Label) alex1$outcome<-as.numeric(alex1$Label) alex1$outcome[1:20] #self-organizing maps(unsupervised learning) library("kohonen") #SOM, the supervised learning, train the map using outcome as the class variable. set.seed(13) final.xyf<- xyf(data=as.matrix(alex1[,c(1:256)]), Y=classvec2classmat(alex1$outcome), xweight = 0.99, grid=somgrid(20, 30, "hexagonal")) outcome.xyf <- predict(final.xyf)$unit.p...

...ools that work with all clustering algorithms, and some that are tailored for particular ones. Generic tools allow you to animate between clusterings (see ?cfly_animate) and produce common static graphics (?cfly_dist, ?cfly_pcp). Specific algorithms are available for: * Self organising maps (aka Kohonen neural networks), ?ggobi.som. Displays the self organising map/net in the original space of the data. * Hierarchical clustering, ?hierfly. Connects data points with lines like a dendrogram, but in the high-dimensional space of the original data * Model based clustering, ?mefly. Adds ellipsoids f...

...ools that work with all clustering algorithms, and some that are tailored for particular ones. Generic tools allow you to animate between clusterings (see ?cfly_animate) and produce common static graphics (?cfly_dist, ?cfly_pcp). Specific algorithms are available for: * Self organising maps (aka Kohonen neural networks), ?ggobi.som. Displays the self organising map/net in the original space of the data. * Hierarchical clustering, ?hierfly. Connects data points with lines like a dendrogram, but in the high-dimensional space of the original data * Model based clustering, ?mefly. Adds ellipsoids f...