search for: silinfo

hello, i'm pete ,how can i order rows of matrix by max to min value? I have a matrix of membership degrees, with 82 (i) rows and K coloumns, K are clusters. I need first and second largest elements of the i-th row. for example 1 0.66 0.04 0.01 0.30 2 0.02 0.89 0.09 0.00 3 0.06 0.92 0.01 0.01 4 0.07 0.71 0.21 0.01 5 0.10 0.85 0.04 0.01 6 0.91 0.04 0.02 0.02 7 0.00 0.01 0.98 0.00 8 0.02

...ed by the sum of these differences I need a final vector composed of the indexes for each clustering (K=2,...,K.max=6). There is a method, i think that is classe.memb, but i can't to solve problem because trasformation of the membership degrees matrix( (ris$membership) and of list object (ris$silinfo), does not permit me to use classe.memb propertyes. . ??(u?1-u?2)s?/??(u?1-u?2) > head(t(A.sort)) membership degrees table ordering by max to min value [,1] [,2] [,3] [,4] 1 0.66 0.30 0.04 0.01 2 0.89 0.09 0.02 0.00 3 0.92 0.06 0.01 0.01 4 0.71 0.21 0.07 0.01 5 0.85 0.10 0.04 0.01 6...

Hello R-listers, I'm having trouble accessing "sub" objects ("attributes"?), e.g., "x$silinfo$avg.width" using the /get() /command; I'm using/ get()/ in a loop as illustrated in the following code: #FIRST MAKE CLUSTERS of VARYING k /for (i in 1:300){ assign(paste("x.",i,sep=""),pam(x,i)) #WORKS FINE }/ #NEXT, TAKE LOOK AT AVE. SILHOUETTE VALUE FOR EACH k...

...ybe 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 export "clustering" and "data" to a new text file so I try > write.table(myclara$data,"cluster.dat") > write.table(myclara$clustering,"cluster.dat",append=TRUE) Variable data is properly exported but clustering is...

...y the way, I have alot of missing values in my dataset, coded as "NA", so some software packages don't work. Here is the code I've been using: library(cluster) avgsil <- c() for (k in kseq){ clarares <- clara(data, k, rngR = TRUE) savg <- clarares$silinfo$avg.width print(c(k,savg)) avgsil[k] <- savg } k<-kseq plot(k,avgsil[k]) lines(k,avgsil[k]) Sincerely, Andrew McSweeny grad student Medical University of Ohio [[alternative HTML version deleted]]

Hi, I would like to know if someone knows an extended implementation of k-means in R to find appropriate number of clusters for a given k-dimensional data. Also, I am working on clustering for forecasting, if someone is interested or has knowledge on implementational details please mail me, I would appreciate it. Regards Skanda Kallur "Cogito, ergo sum" (I think, therefore I

...: Clustering vector: Cluster sizes: Best sample: Available components: [1] "sample" "medoids" "i.med" "clustering" "objective" "clusinfo" "diss" [8] "call" "silinfo" "data" But "kmeans" has: K-means clustering with 2 clusters of sizes 50, 50 Cluster means: Clustering vector: Within cluster sum of squares by cluster: Available components: [1] "cluster" "centers" "withinss" "size&quo...

...y the way, I have alot of missing values in my dataset, coded as "NA", so some software packages don't work. Here is the code I've been using: library(cluster) avgsil <- c() for (k in kseq){ clarares <- clara(data, k, rngR = TRUE) savg <- clarares$silinfo$avg.width print(c(k,savg)) avgsil[k] <- savg } k<-kseq plot(k,avgsil[k]) lines(k,avgsil[k]) Sincerely, Andrew McSweeny grad student Medical University of Ohio [[alternative HTML version deleted]]

...[2,] 9 9 Clustering vector: [1] 1 1 1 1 1 2 1 2 2 2 1 1 Objective function: build swap 0.01873272 0.01620992 Available components: [1] "medoids" "id.med" "clustering" "objective" "isolation" [6] "clusinfo" "silinfo" "diss" "call" > ndex.G1(as.matrix(alpha.vec),cl$cluster,d=dist.mat,centrotypes="medoids") Error: could not find function "ndex.G1" > index.G1(as.matrix(alpha.vec),cl$cluster,d=dist.mat,centrotypes="medoids") Error in cente...