similar to: Clustering with clara

HI R users With clara function I get a data frame (maybe this is not the exact word, I'm new to R) with the following variables: > names(myclara) [1] "sample" "medoids" "i.med" "clustering" "objective" [6] "clusinfo" "diss" "call" "silinfo" "data" I want to

Hello R users It's some time I am playing with a dataset to do some cluster analysis. The data set consists of 14 columns being geographical coordinates and monthly temperatures in annual files latitutde - longitude - temperature 1 -..... - temperature 12 I have some missing values in some cases, maybe there are 8 monthly valid values at some points with four non valid. I don't want to

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've also read something

Hi everyone As I couldn't succeed with manual installation of Rmpi I decided to start again from the beginning. I removed R and MPICH in my Ubuntu Hardy installation. Then, to avoid any dependencies problems I have installed MPICH and R from synaptic, not from sources. But now I can't install Rmpi. An error message appears when trying to install Rmpi, you can find in

Hi everyone I want to install Rmpi to use R in parallel mode in a Linux cluster (Ubuntu, Hardy Heron). It seems to be properly installed but a problem appears when loading Rmpi library. R version 2.11.1 (2010-05-31) > library("Rmpi") Error: package 'Rmpi' was built before R 2.10.0: please re-install it Should I remove R-2.11 and install R-2.10? I have tried to

Hi R-users I'm a beginner with R and statistics, so I need some help to start my data analysis. I've been reading some docs and tutorials on R and cluster analysis. I've got a large dataset (102000 points) with values of longitude, latitude and temperature and want to see if I can find groups (clusters). Following some tutorials I can look for principal components but get an error

Hi everyone I am new to R and have a question about missing values. I am trying to do a cluster analysis of monthly temperatures and my data are 14 columns with spatial coordinates (lat,lon) and 12 monthly values: /lat - lon - temp1 - //temp2 - temp3 - .... - //temp12/ If I omit missing values (my missing values are 99.00) with /mydata <- na.omit(mydata)/ every row with a

Maybe the following article is of interest for you (co-authored by P.J. Rousseeuw, like the book you mentioned): http://www.jstatsoft.org/v01/i04/paper/clus.pdf -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:

Moin, is there any possibility to choose the input variables which are involved in the analysis, " ..., and each column correspondends to a variable. ..." (R-Reference-Manual) or do I have to delete them from the data.frame? An then I'd like to get the original dataset with the classification of the cluster, at the moment i do it this way clusterFrame <-

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

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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 is possible. Essentially I am trying to

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

Greetings, Experimenting with the cluster package, and am starting to scratch my head in regards to the *best* way to standardize my data. Both functions can pre-standardize columns in a dataframe. according to the manual: Measurements are standardized for each variable (column), by subtracting the variable's mean value and dividing by the variable's mean absolute deviation. This

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

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

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

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 mean absolute deviation. If we note STAND = TRUE, I suppose that

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 windows computer

I wish to make modifications to the plot.pedigree function in the kinship package. My attempts to contact the maintainer have been unsuccessful, but my question is general, so specifics of the kinship package might not be an issue. My first attempt was to make a new function Plot.pedigree in the .GlobalEnv which mostly achieved what I wanted to. However, I'm sure that's not the tidiest