similar to: k-means++

Dear All, I have a dissimilarity matrix which I happily convert to a distance object by running: X <- as.dist(Y) and I can happily now run either hclust(X) or agnes(X). So that the various bits of output are labelled correctly I would dearly like to be able to give names to the columns and rows of X, as would happen if I ran: mydata<-read.table("clipboard",header=T)

I'm writing R code to calculate Hierarchical Social Entropy, a diversity index that Tucker Balch proposed. One article on this was published in Autonomous Robots in 2000. You can find that and others through his web page at Georgia Tech. http://www.cc.gatech.edu/~tucker/index2.html While I work on this, I realize (again) that I'm a C programmer masquerading in R, and its really

Hi all, I wanted to run the hclust (or any other clustering algorithm) on a distance matrix. I have formed the distance matrix as: distmat: a b c d e a 0.00 0.96 1.60 1.60 1.68 b 0.96 0.00 0.96 1.80 2.64 c 1.60 0.96 0.00 0.84 1.80 d 1.60 1.80 0.84 0.00 0.96 e 1.68 2.64 1.80 0.96 0.00

Hi All, i've problem to understand how to work with R to generate a hierarchical clustering my data are in a csv and looks like : idcode,count,temp,sal,depth_m,subs 16001,136,4.308,32.828,63.46,47 16001,109,4.31,32.829,63.09,49 16001,107,4.302,32.822,62.54,47 16001,87,4.318,32.834,62.54,48 16002,82,4.312,32.832,63.28,49 16002,77,4.325,32.828,65.65,46 16002,77,4.302,32.821,62.36,47

Dear all. I am searching for KMeans ++ for R. I cannot find it. Do you know any package with it? Best regards, Rui

Hi all, I have a dataframe of rownames that I would like to extract from a larger matrix to form a new matrix. I have tried to use subset, in this manner x<-subset(largematrix, rownames$names=largematrix$rownames) where largematrix is the larger matrix and rownames$names is the dataframe with the row names of the rows I want to extract from the larger matrix. Of course, I get error

Hello - I am currently simulating bivariate AR(1) time series data and have the following line in my code: Px=spec.pgram(ts.union(X,XX),spans=c(?,?)) The spans option is where I enter in the vector containing the Daniell smoother numbers, but I don't know what a Daniell smoother is (hence the question marks). Can somebody please tell me? Is there another option where I can simply enter in

Dear useRs, I have a very basic question. I have a distance matrix and i skipped the upper part of it deliberately. The distance matrix is 1000*1000. Then i used "min" command to extract the lowest value from that matrix. Now i want to know what is the location of that lowest element? More precisely, the row and column number of that lowest element. Thanks in advance elisa

On Sun, Mar 6, 2016 at 7:17 AM, James Aylett <james-xapian at tartarus.org> wrote: > On Sat, Mar 05, 2016 at 10:58:43PM +0530, Richhiey Thomas wrote: > > K-Means or something related certainly seems like a viable approach, > so what you'll need to do is to come up with a proposal of how you'd > implement this in Xapian (either with reference to the previous work, >

I'm trying to perform a mantel test that ignores specific pairs in my distance matrices. The reasoning is that some geographic distances below a certain threshold suffer from spatial autocorrelation, or perhaps ecological relationships become less relevant that stochastic processes above a certain threshold. The problem is that I can't find a way to do it. If I replace values in either or

Hello All,I am Nirmal Singhania from NIIT University,India. I am interested in Clustering of search results Topic. I have been in field of practical machine learning and information retrieval from quite some time. I took various courses/MOOC on Information retrieval and Text Mining and have been working on real life datasets(KDD99,AWID,Movielens). Because the problems you face in real life ML/IR

Hello devs, I am Richhiey Thomas, pursuing my third year of undergraduate studies in Computer Science from Mumbai University. I had gone through the project list for this year and the project idea based on clustering caught my attention. I spoke to Assem Chelli on IRC who guided me to the code and got me started. I started going through the code and have successfully built Xapian on my machine.

Tf-idf is most used used weighting scheme is easy to understand and has been used in other frameworks like lucene and many other places. okapi bm25(implemented in xapian) is theoretically better/improved measure than tf-idf and i am looking into various other weighting scheme which are there in xapian or can be implemented like TF-ICF(term frequecy inverse corpus frequency),TF-RF(term

I'm working with capscale and permutest for the first time, and having trouble getting statistical analyses for more than one constraining variable. I've read the documentation, but setting first=FALSE or using by="axis" doesn't seem to be helping. capscale seems to be fine, I receive output for more than one constrained axis. What am I doing wrong?

Hi all, Thanks for your help in generating the matrix of distance vs correlation. I did it using plot(as.vector(as.matrix(cormat)), as.vector(as.matrix(distmat))) Now I want to quantitate the same. May be on linear regression or some other statistical functions. I have tried using linmod for linear regression. But as I have two matrices in the form of the dataframes, I'm wondering if it

yo, ive been using the fstack protector for a while now and it worked fine until i was gonna compile 4.8p3 then i got these errors, sio.o(.text+0x18b7): undefined reference to `__guard' sio.o(.text+0x1da9): undefined reference to `__guard' sio.o(.text+0x1db9): undefined reference to `__stack_smash_handler' vga_isa.o: In function `isavga_probe': vga_isa.o(.text+0x10): undefined