similar to: "FANNY" function in R package "cluster"

Hello, I would like to use my own dissimilarity matrix in a PAM clustering with method "pam" (cluster package) instead of a dissimilarity matrix created by daisy. I read data from a file containing the dissimilarity values using "read.csv". This creates a matrix (alternatively: an array or vector) which is not accepted by "pam": A call

Hi, I'm trying to use a similarity matrix (triangular) as input for pam() or fanny() clustering algorithms. The problem is that this algorithms can only accept a dissimilarity matrix, normally generated by daisy(). However, daisy only accept 'data matrix or dataframe. Dissimilarities will be computed between the rows of x'. Is there any way to say to that your data are already a

Full_Name: Guan-Hua Huang Version: 2.0.1 OS: Linux Submission from: (NULL) (140.113.114.123) I install the package cluster by using install.packages("cluster"). After install it, it runs fine for function clara, but it does not work for function fanny. I did the following things: library(cluster) set.seed(21) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),

Hello List, My question is an elementary one. I have run a fuzzy kmeans cluster using FANNY to group freshwater fish assemblages. I then went in the field to validate that classification and have retrieved new assemblage data for a new suite of streams. Therefore I would like to use Predict to determine how well the original clustering fits the new data. However I have not figured out a

Dear All, My R version: 2.0.1 ; OS using: Linux. I install the package cluster by using install.packages("cluster"). After install it, it runs fine for function clara, but it does not work for function fanny. I did the following things: library(cluster) set.seed(21) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),cbind(rnorm(15, 5, 0.5), rnorm(15, 5, 0.5)),cbind(rnorm(

Hi, I am using fanny and I have estrange results. I am wondering if someone out there can help me understand why this happens. First of all in most of my tries, it gives me a result in which each object has equal membership in all clusters. I have read that that means "the clustering is entirely fuzzy". Looking at the graphics it is really difficult to understand how objects with so

Hi, Many apologies for sending this twice. I accidentally hit the send button before I finished writing my mail. I am new to R and I hope someone can help me with my problem. I am trying to draw a side by side barplot. There is a main experiment and there are many sub experiments within the main experiment. I would like to draw a bar plot showing the number and type of sub_experiments done for

Dear R people, I need to do some work with clustering, but know next to nothing about it at present. R has (at least) three clustering packages, cluster, mclust, cclust. I was wondering if someone can direct me to some good books where I could find documentation and background on the functions in these packages. The html help in these packages lists the following as references. Can people

I have "small" problem ... with the cluster library each time I try to use the "agnes","pam","fanny" functions with more than 20000 elements I get the following error: >Error in vector("double", length) : negative length vectors are not allowed >In addition: Warning message: >NAs introduced by coercion But with the clara

A small comment: The code of Agnes is written in Fortran. Following book give more details: Kaufman, L. and Rousseeuw, P.J. (1990). _Finding Groups in Data: An Introduction to Cluster Analysis_. Wiley, New York. The 'hclust' function is based an Algorithm contributed to STATLIB by F. Murtagh and the code is written in C. Probably the differences between agnes and hclust causes

Hi all, let's say I have matrix People Desc Value Mary Height 50 Mary Weight 100 Fanny Height 60 Fanny Height 200 Is there a quick way to form the following matrix? People Height Weight Mary 50 100 Fanny 60 200 (Assuming I don't know the length of people/desc and let's say these are characters matrix.. I tried

Hello, Instead of receiving only one message when somebody send a question or a answer, I receive 2 messages with exactly the same contents inside. Is it the same for you? Thank you, Fanny -------------------------- Fanny AZIZA École Nationale Vétérinaire d'Alfort Mail: faziza@vet-alfort.fr Tél. 01 43 96 70 33 [[alternate HTML version deleted]]

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 =

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I've done a little digging, but I haven't been able to find an MPI or snow (or any other distributed processing) implementation of fanny (from cluster) or cmeans. Is anyone aware of some implementations or addons which I've missed? [I know of doi://10.1007/978-3-540-71351-7; but that's not for R] Don Armstrong [Currently not subscribed; M-F-T: set accordingly.] -- Certainly

Hello, Could someone please let me know the procedure for determining the 'best' solution with regards to the number of clusters using the Fanny algorithm for computing fuzzy clusters? The function requires a specification of the number of clusters a priori, but I am interested in determining what number of clusters would result in the ideal fit with the data. Any help/advice/pointers to

Hello, I want to make a fuzzy classification from a dissimilarity matrix (calculated with daisy from package 'cluster'). I have tried to use fanny (package cluster) but I have the same problems than described in a previous message (http://tolstoy.newcastle.edu.au/R/help/05/05/4546.html) i.e. it always gives me two clusters in the results (even if k is different from 2) with the same

Dear all, I'm trying to obtain a fuzzy clustering with fanny from the cluster package, using a given set of data. That worked just fine. I have another separate sample of data from the same problem. For each case in this new sample I would like to know their membership coefficients with respect to the clustering obtained with the first dataset. In effect I want to have a kind of prediction

Greetings, I am reasonably experienced with R but I recently tried to do some clustering using the "cluster" package, in order to see if it would help. I only tried this once with the 1.3.1 version and it worked (I don't quite remember which method I used). Now, I tried with the 1.4.0 version and no clustering function seems to work with matrices that contain NAs, even though

Hello, i use i.e. the cluster-package and the fanny-object to construct some cluster's and get the membership'S for every "Person" & Cluster ! My finally problem is to match efficient the data and the results's togehter in one table! Until now i use the ODBC-Package and save both in a access-file and copy them together, but i can't be sure that the sorting is the