search for: clara

Dear all, I'm trying to estimate clusters from a very large dataset using clara but the program stops with a memory error. The (very simple) code and the error: mydata<-read.dbf(file="fnorsel_4px.dbf") my.clara.7k<-clara(mydata,k=7) >Error: cannot allocate vector of size 465108 Kb The dataset contains >3,000,000 rows and 15 columns. I'm using a win...

Greetings, I have had good success using the clara() function to perform a simple cluster analysis on a large dataset (1 million+ records with 9 variables). Since the clara function is a wrapper to pam(), which will accept known medoid data - I am wondering if this too is possible with clara() ... The documentation does not suggest that this i...

...ean for a subset of observations? For example, suppose my data looks like this: OBS NAME SCORE 1 Tom 92 2 Tom 88 3 Tom 56 4 James 85 5 James 75 6 James 32 7 Dawn 56 8 Dawn 91 9 Clara 95 10 Clara 84 Is there a way to get the mean of the SCORE variable by NAME but only when the number of observations is equal to 3? In other words, is there a way to get the mean of the SCORE variable for Tom and James, but not for Dawn and Clara? Thank you. -- Geoffrey Smith Vi...

Hi everyone I have a question about clustering. I've managed using CLARA to get a clustering analysis of a large data set. But now I want to find which is the right number of clusters. The clara.object gives some information like the ratio between maximal and minimal dissimilarity that says (maybe if lower than 1??) if a cluster is well-separated from the other. I'...

Dear All , Since dissimilarity is one of quality measures in clustering , I'm trying to access to the sum of dissimilarity as a whole measure. But after running my data using CLARA I obtain : 1128 dissimilarities, summarized : Min. 1st Qu. Median Mean 3rd Qu. Max. 0.033155 0.934630 2.257000 2.941600 4.876600 8.943700 But I can not find the sum of dissimilarity.How can i access to it? Thanks a lot Safari __________________________________________________...

Hello everyone I am trying to use CLARA method for finding clusters in my spatial surface temperature data and noticed one problem. My data are in the form lat,lon,temperature. I extract lat,lon and cluster number for each point in the dataset. When I plotted a map of cluster numbers I found empty areas in the map. The point is that the...

I need informations about the clara routine. The on-line doc say that the argument stand is a logical, indicating if the measurements in x are standardized before calculating the dissimilarities. Measurements are standardized for each variable (column), by subtracting the variable's mean value and dividing by the variable's m...

Dear Clara, Thanks for the reply. I am forwarding your message to the list, ok. When I wrote was a way of get further information to help the helpers. happy holidays, milton ---------- Forwarded message ---------- From: Clara Brück <clara_brueck@web.de> Date: 2009/12/30 Subject: Re: [R] Negbin Error...

Hi, i want a cluster-analysis with clara, but getting an error because in cldat are NA's. Error in clara(cldat[, 1:3], 4) : Each of the random samples contains objects between which no distance can be computed. cldatx <- subset(cldat,select=c(A,B,C)) cldaty <- na.omit(cldatx) Now , clara works but cldat has ~193.000 obs a...

...have a large data matrix (68x13112), each row corresponding to one observation (patients) and each column corresponding to the variables (points within an NMR spectrum). I would like to carry out some kind of clustering on these data to see how many clusters are there. I have tried the function clara() from the package cluster. If I use the matrix as is, I can perform the clara analysis but when I call clusplot() I get this error: Error in princomp.default(x, scores = TRUE, cor = ncol(x) != 2) : 'princomp' can only be used with more units than variables Then, I reduce the dimensi...

...orph <- data.frame(cbind(x$er, x$crosc, x$longc, x$slope/max(x$slope), x$profc, x$minic, x$maxic)) names(morph) <- c("er","crosc","longc","slope_n","profc","minic","maxic") print("perform the clustering") morph.clara <- clara(morph, k=5, stand=F) x$morph_class <- morph.clara$clustering print("send result back to GRASS") rast.put6(x,"morph", zcol="morph_class") during the step : ....perform the clustering after a lot of time, i've this error: Errore in sprintf(fm...

Folks, I''m happy to report that dates have been finalized for the next Xen Summit: November 14-16 2007; Santa Clara CA, USA Sun Microsystems have kindly agreed to host the event at their Santa Clara campus. The plan is to start at 1pm on Wednesday the 14th, then run until lunchtime on Friday. The next steps are to put together a program committee and send out a formal Call For Papers, but it would be great...

Folks, I''m happy to report that dates have been finalized for the next Xen Summit: November 14-16 2007; Santa Clara CA, USA Sun Microsystems have kindly agreed to host the event at their Santa Clara campus. The plan is to start at 1pm on Wednesday the 14th, then run until lunchtime on Friday. The next steps are to put together a program committee and send out a formal Call For Papers, but it would be great...

...<- data.frame(cbind(x$er, x$crosc, x$longc, x$slope/max(x $slope), x$profc, x$minic, x$maxic)) names(morph) <- c ("er","crosc","longc","slope_n","profc","minic","maxic") print("perform the clustering") morph.clara <- clara(morph, k=5, stand=F) x$morph_class <- morph.clara$clustering print("send result back to GRASS") rast.put6(x,"morph", zcol="morph_class") during the step : ....perform the clustering after a lot of time, i've this error: Errore in sprintf(fm...

...23.7813 8.0000 --- > [25] 4.0000 5.5000 5.0000 22.3438 5.0000 12.5000 23.7812 8.0000 559c559 < [65] 5.0000 19.1250 2.0000 6.0000 10.5000 4.0000 15.0000 41.5313 --- > [65] 5.0000 19.1250 2.0000 6.0000 10.5000 4.0000 15.0000 41.5312 OK Running `clara-NAs.R' Comparing `clara-NAs.Rout' to `clara-NAs.Rout.save' ...36,47c36,47 < 6 NaN NaN NaN NaN NaN < 7 40 45 12 56 65 NaN < 8 8 21 46 52 33 NaN 34 < 9 23 18 64 41 22 NaN 63 29 < 10 19 30 42 61 44 NaN 33 13 42 < 11 165 178 270 209 190 NaN...

...f -Heinrich. > -----Urspr?ngliche Nachricht----- > Von: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] Im Auftrag von Fucang Jia > Gesendet: Donnerstag, 11. Dezember 2003 14:37 > An: r-help at stat.math.ethz.ch > Betreff: [R] Paper on PAM and Clara > > > Hi, everyone, > > I found that Clara and Pam is very useful in large data > clustering. So I > want to learn more about it. But as far as I know, the idea > is comes the > authors' book "Finding groups in data: an introduction to > cluster analys...

Hello list, I am new to R, so if the question is rather silly, please ignore it. I was wondering wether it would be possible to use the models generated by pam, clara and the like as predictors? Scanning through the available documentation shed no light (for me) upon the subject. Regards, Renald

Hi there, I use function "kmeans" and "clara" to cluster one flow cytometry dataset. By using function "plot", the clusters got from "clara" can be graphed, while "kmeans" not. How can I get the plot of the clusters of "kmeans"? And, I hope to compare the two methods "kmeans" and &quo...

Hi everybody, just a quick reminder that the Xen Hackathon is in Oracle, March 6-8, Santa Clara, CA, USA. We have originally planned for about 25 people, but already we have 14 people signed up. If you are planning to attend please sign up quickly, such that I get a feeling for the number of attendees. I can then go back to Oracle and see whether we can accommodate more people than we pla...

...at least one change in labour market status is included in the data set. To analyse sub sets of the data, I have used daisy in the cluster-package to create a distance matrix and then used pam (or pamk in the fpc-package), to get a k-medoids cluster-solution. Now I want to analyse the whole set. clara is said to cope with large data sets, but the first step in the cluster analysis, the creation of the distance matrix must be done by another function since clara only works with numeric data. Is there an alternative to the daisy -> clara route that does not require as much RAM? What functions...