similar to: compare quality of clustering methods?

Hello all, I would like to compare the similarity of two cluster solutions using a validation criteria (such as Hubert's gamma coefficient, the Dunn index the corrected rand index and so on) I see (from here:http://www.statmethods.net/advstats/cluster.html) that the function cluster.stats() in the fpc package provides a mechanism for comparing 2 cluster solutions - *BUT* - it requires me to

Hi, I am trying to do a Principal component analysis on histogram data. Basically, I have a group of subjects and for each of them, I have a column of bin-counts (vis-a-vis intervals) and a corresponding column of frequencies (or normalized frequencies). The bin counts are the same for all the subjects. I also have a group-averaged histogram (with the same bin counts and a column of frequencies)

Hi R, I was using 'as.dendrogram' with the DIST coefficient, where the smaller values of the DIST coefficient, say that the objects are closer to each other, while the larger values of the coefficient say that the objects are far from each other. But now, I have my coefficient as the DICE coefficient(in some sense similar to correlation coefficient), where the larger coefficient

Hi, I have seen that R has a implementation of decision trees; however, after I have the tree with the classification: R Quinlan's trivial example of the "golf" decision tree. Outlook Temperature Humidity Windy PlayDontPlay 1 sunny 85 85 false DontPlay 2 sunny 80 90 true DontPlay 3 overcast 83 78 false Play 4 rain 70 96 false Play ... What's next? I mean, what is this

I run the following code: library(rpart) data(kyphosis) fit <- rpart(Kyphosis ~ ., data=kyphosis) plot(fit) text(fit, use.n=TRUE) The text labels represent the count of each class at the leaf node. Unfortunately, the numbers are rounded and in scientific notation rather than the exact number of examples sorted by that node in each class. The plot is supposed to look like

Hi all, I have a question about hist() 1) > t1 <- hist(c(1,2,3,4,5)) > t1 $breaks [1] 1 2 3 4 5 $counts [1] 2 1 1 1 why is there 2 counts for 1? And should the counts be '1 1 1 1 1' ? Is there any other function to count frequency of discrete data? Thanks. -k [[alternative HTML version deleted]]

Dear All, In a package, I want to use PCA function. The structure I used follow this page: http://www.statmethods.net/advstats/factor.html. fit<-principle(mydata, nfactors=9, rotation=TRUE) or: result<-PCA(mydata) But I don't known why R language in my computer noticed: "not found principle", "not found PCA". I download and installed

I ran this code (several times) from the Quick-R web page ( http://www.statmethods.net/advstats/cart.html) but my cross-validation errors increase instead of decrease (same thing happens with an unrelated data set). Why does this happen? Am I doing something wrong? # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start,

I am interested in applying a "classification tree" analysis where the response variable is a censored variable (survival data). I've discovered the package 'party' through this page: http://www.statmethods.net/advstats/cart.html. However, as my sample is not very big I would like to apply 'bootstrap' and use 'random forests', but with my censored response

I am trying to create a classification tree using either tree or rpart functions but when it comes to plotting the results the formatting I get is different than what I see in all the tutorials (like http://www.youtube.com/watch?v=9XNhqO1bu0A or http://www.youtube.com/watch?v=m3mLNpeke0I&feature=related or http://www.statmethods.net/advstats/cart.html "tree for kyphosis"). I am

Hi, This is my first time so bear with me if I do anything silly. I'll learn! I'm a relatively new user of R as well so will appreciate any help. I have a data set in the form Trial.Group MeanHeart Rate Upper confidence level Lower confidence level 333subj: 0-5 M 80 60 120etcetc I want to plot a graph that has Trial.Group on the x axis(names, not just an

Hi, I'm stuck with parsing data into R for heatmap representation. The data looks like: 1 id1 x1 x2 x3 .... x20 2 id1 x1 x2 x3 .... x20 3 id1 x1 x2 x3 .... x20 4 id1 x1 x2 x3 .... x20 ......... 348 id2 x1 x2 x3 .... x20 349 id2 x1 x2 x3 .... x20 350 id2 x1 x2 x3 .... x20 351 id2 x1 x2 x3 .... x20 ......... The data is sorted for the IDs (id1,id2 .....id40) and I like to

A reworked version of 3 out of 4 patches mentioned earlier. [1/4]: Fixes nearly all piglit vertprog testcases, due to now being able to pass the results on to the fragment shader. V2: rename samplers to texcoords. [2/4]: Fixes shader compiler assertion errors, as some source registers do not exist for certain operations. Fixes several piglit tests when mesa is compiled with --enable-debug [3/4]:

Thanks to Mr.Liviu Androvic and Mr.Richard Rowe helped me in PCA. Because I have just learn R language in a few day so I have many problem. 1) I don't know why PCA rotation function not run although I try many times. Would you please hepl me and explain how to read the PCA map (both of rotated and unrotated) in a concrete example. 2) Where I can find document relate: Plan S(A), S(A*B),

Hi All, I have got matrix 'data' of dimension 22000x600. I want to make 50 independent samples of dimension 22000x300 from the original matrix 'data'. And then want to calculate pearsons CC for each of the obtained 50 matrices. It seems it is possible to do this using 'boot' function from library boot but I am not able to figure out how? I am really stuck. Please help!

Hi, I'm currently trying to find/define a relationship between one dependent and several independant variables. The problem is that i cannot use the normal multiple regression/correlation in Spss because the data is not normal distributed. i calculated the spearman roh and Kendalls tau Correlation and also some partial correlations in R. Now i wanna find out the the multiple correlation

I have an exercise. With 3 kinds of yohourt a,b,c. There are 25 participatients estimate 3 norms: taste (va,vb,vc), structure (ca,cb,cc) and price (ga,gb,gc) and give the mark from 1 to 5. I don't know how to PCA this data. Please help me! I attached the data file follow: Va Vb Vc Ca Cb Cc Ga Gb Gc 4 2 4 5 5 5 4 4 2 2 2 4 3 2 5 4 5 1 2 2 1 2 3 3 3 1 4 1 1 2 2 3 3 4 3 2 3 4 4 4 3 1 2 1 2 1 1 1

Hi I have a question, as im not able to import a csv file which contains a big dataset(100.000 records) someone knows how many records R can handle without giving problems? What im facing when i try to import the file is that R generates more than 100.000 records and is very slow... thanks a lot!!!

Hi all, In R, is there some functions or ways to create a Clustered-Stacked Column Chart as the example in the following page http://peltiertech.com/Excel/ChartsHowTo/ClusterStack.html? I have browsed the R Graph Gallery (http://addictedtor.free.fr/graphiques/) and searched the R site, and didnot find an appropriate method to do it. Anybody has met this problem before? Thanks a lot.

For all these patches I'd say: testers are welcome. The first three patches seem good enough to push as we speak IMHO (so if you agree, go ahead!), whereas for the fourth I don't know if this is the desired way to fix. The result of these four patches is that NV34 gives a nearly-correct desktop experience, where only some fading animations appear broken. It's quite useable now! [1/4]: