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Dear All: I'm a newbie to R and chemometrics. Now I'm trying apply bclust on fuzzy c-means like this: >bc1 <- bclust(iris[,1:4], 3, base.centers=20,iter.base=100, base.method="cmeans") Committee Member: 1(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)Erro r in bclust(iris[, 1:4], 3, base.centers = 20, iter.base = 100, base.method =

A new version of e1071 has been released to CRAN which should be much easier to install on a lot of platforms because reading/writing PNM images has been moved to the pixmap package, hence there are no longer dependencies on external libraries and no configure mechanism. For the authors, Fritz Leisch ********************************************************** Changes in Version 1.2-0: o

Hi there, I'm doing some clustering analysis and try to find all the algorithms related to clustering in R. Here is the list of the algorithms I found. But I'm not sure if It's the complete list. Could you please check it and see if there're other ones? Thank you very much! P.S.: List of the algorithms related to clustering: (1) Hierarchical methods hclust

Hi All, For the function "bclust"(e1071), the argument "base.method" is explained as "must be the name of a partitioning cluster function returning a list with the same components as the return value of 'kmeans'. In my understanding, there are three partitioning cluster functions in R, which are "clara, pam, fanny". Then I check each of them to

Dear all, I have a problem with the function "bagged clustering" of package e1071. When I try to run the example of bagged clustering with the iris data : data(iris) bc1 <- bclust(iris[,1:4], 3, base.centers=5) I got the following message error : Loading required package: class Committee Member: 1(1) 2(1) 3(1) 4(1) 5(1) 6(1) 7(1) 8(1) 9(1) 10(1)Error in bclust(iris[, 1:4], 3,

Hi everyone, Currently i'm trying to understand the bagged clustering algorithm, bclust {e1071}. When I run the given example in the help file (as below) data(iris) bc1 <- bclust(iris[,1:4], 3, base.centers=5) plot(bc1) and plot the bclust object, 2 graphs are produced. The first is a dendrogram, but what is the second plot? The axes are not labelled and what do the two

Hi, I am out of town and will get back to you on the 13th of July. Leo >>> "r-help at stat.math.ethz.ch" 06/27/03 00:32 >>> Send R-help mailing list submissions to r-help at stat.math.ethz.ch To subscribe or unsubscribe via the World Wide Web, visit https://www.stat.math.ethz.ch/mailman/listinfo/r-help or, via email, send a message with subject or body

Hello, I am trying to install R packages under linux, some of the packages can not be installed and I got the following error, could anybody give me suggestion on where the problem is and how to fix it? Thanks-e > .libPaths() [1] "/usr/lib64/R/library" [2] "/usr/share/R/library" [3]

Hi, I got command to execute R code from Mark. but it was showing error.. Error in library(hopach) : there is no package called 'hopach' Does it mean this library hopach is not installed. But I have installed complete Bioconductor package. I am confused. can you help me in this thanks Regards, -- Prateek Singh Final year Bioinformatics(BTech) Vellore Institute Of Technology

Hello everybody, I have a problem with the commando of boxplot -bclust. http://127.0.0.1:13155/library/e1071/html/boxplot.bclust.html > data(iris) > bc1 <- bclust(iris[,1:4], 3, base.centers=5) Committee Member: 1(1) 2(1) 3(1) 4(1) 5(1) 6(1) 7(1) 8(1) 9(1) 10(1) Computing Hierarchical Clustering > boxplot(bc1) Warnmeldungen: 1: In if (x$datamean) { : Bedingung hat Länge > 1 und

Hi, I have a very large dataset of 3008 individuals and 800 numerical variables. In fact it is a table of 3008 36-monthes multivariated time series that I would like to classify with an unsupervised algorithm I had a look at the function kkmeans of e1071 package, which seems to be a kernel weighted version of the algorithm algorithm, and the bclust from the same package which does bootstrapping

Hello R-community: Much of the time I want to use loops to look at graphs, etc. For example, I have 25 plots, for which the names are m.1$medoids, m.2$medoids, ..., m.25$medoids. I want to index the object number (1:25) as below (just to show concept). for (i in 1:25){ plot(m.i$medoids) } I've tried the following, with negative results for ...

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

Hi All, Could you please help with the error I get from the following codes? > Library(cluster) > data(iris) > bc1 <- bclust(iris[,2:5], 3, base.method="clara", base.centers=5) Then I got: "Committee Member: 1(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) Error in bclust(iris[, 2:5], 3, base.method = "clara",

I am using some functions from package clusterSim to evaluate the best clusters layout. Here is the features vector I am using to cluater 12 signals: > alpha.vec [1] 0.8540039 0.8558350 0.8006592 0.8066406 0.8322754 0.8991699 0.8212891 [8] 0.8815918 0.9050293 0.9174194 0.8613281 0.8425293 In the following I pasted an excerpt of my program:

Pues no lo sé. Es algo del código de RandomForest, supongo. Quoting Jesús Para Fernández <j.para.fernandez en hotmail.com>: > U es un dataframe? > > Obtener Outlook para Android<https://aka.ms/ghei36> > > ________________________________ > From: R-help-es <r-help-es-bounces en r-project.org> on behalf of > Manuel Mendoza <mmendoza en mncn.csic.es>

Tuve que dejar, de momento, lo del "loop con matriz que cambia de nombre" por algo más urgente, y me salió otro problema. Hago un cmeans con el paquete e1071; cl<-cmeans(Data,i,20,verbose=F,method="cmeans",m=2) y me da este error: Error in apply(u, 1, which.max) : dim(X) must have a positive length. Estoy harto de usar esa línea de código, con dfs iguales a la

Hello all. I wish to run k-means with "manhattan" distance. Since this is not supported by the function "kmeans", I turned to the "pam" function in the "fpc" package. Yet, when I tried to have the algorithm run with different starting points, I found that pam ignores and keep on starting the algorithm from the same starting-points (medoids). For my

Hi, I have 'R' code in file. saved it as exmaple.r here is the code....... library("hopach") GSE <- read.table("gene_expression_data",sep="\t",header=TRUE,row.names=TRUE) gene.dist <- distancematrix(t(GSE),d="euclid") gene.hobj <- hopach(t(GSE), dmat=gene.dist, mss="med") labelstosil(gene.hobj$cluster$label,gene.dist) I dont

Hello, I need a Fuzzy C Means algorithm. I found some documentation about cmeans {e1071} at http://rss.acs.unt.edu/Rdoc/library/e1071/html/cmeans.html Does someone knows where I can find it? Thank you Rui [[alternative HTML version deleted]]