similar to: computationally singular

Dear listers: I have an idea to do the outlier detection and I need to use R to implement it first. Here I hope I can get some input from all the guru's here. I select distance-based approach--- step 1: calculate the distance of any two rows for a dataframe. considering the scaling among different variables, I choose mahalanobis, using variance as scaler. step 2: Let k be the number of

Dear listers: Here I have a question on clustering methods available in R. I am trying to down-sampling the majority class in a classification problem on an imbalanced dataset. Since I don't want to lose information in the original dataset, I don't want to use naive down-sampling: I think using clustering on the majority class' side to select "representative" samples might

hi, is there some good summary on clustering methods in R? It seems there are many packages involving it. And I have two questions on clustering here: 1. Is there a way of evaluate the effecitives (or seperation) of clustering (rather than by visualization)? 2. Is there a search method (like genetic search) which can help find the best subset of attributes which gives best seperation? Thanks,

Hi everybody, I'd like to know if there's an easy way for extracting outliers record from a dataset, in order to perform further analysis on them. Thanks Alessandro

Dear R list, I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data as obtained below: Squared Distance to Species From Species: Setosa Versicolor Virginica Setosa 0 89.86419 179.38471 Versicolor 89.86419 0 17.20107 Virginica 179.38471 17.20107 0 These distances were obtained with proc 'CANDISC'

Hi there, I need a network builder and it can change the node size and color; I am not sure if network package in R can do this or not. The other functions I wanted have been found in that package. BTW, if there is another package in R relating to this, please suggest too. Thanks, Weiwei -- Weiwei Shi, Ph.D Research Scientist "Did you always know?" "No, I did not. But I

Hi, there: I think i need to re-phrase my question since last time I did not get any reply but i think the question is not that hard, probably i did not make the question clear: I want to find cases like 35, 90, 330, 330, 335 from the rest which look like 3, 3, 3, 3.2, 3.3 4, 4.4, 4.5, 4.6, 4.7 .... basically there is one (or more) big 'gap' in the case i seek. thanks, weiwei --

Hi, I have a question on read.table. I have a dataset with 273,000 lines and 195 columns. I used the read.table to load the data into R: trn<-read.table('train1.dat', header=F, sep='|', na.strings='.') I found it takes forever. then I run 1/10 of the data (test) using read.table again. And this time it finished quickly. So, there might be something wrong in my data

Hello R helpers, I'm trying to use Mahalanobis distance to calculate distance of two time series, to make some comparations with euclidean distance, DTW, etc, but I'm having some dificults. I have, for example, two objects: s.1 <- c( 5.6324702, 1.3994353, -3.2572327, -3.8311846, -1.2248719, 0.9894694, -2.2835332, -5.1969285, -5.2823988, -3.1499400, -1.7307950, 2.8221209,

> From: Weiwei Shi > > it works. > thanks, > > but: (just curious) > why i tried previously and i got > > > is.vector(sample.size) > [1] TRUE Because a list is also a vector: > a <- c(list(1), list(2)) > a [[1]] [1] 1 [[2]] [1] 2 > is.vector(a) [1] TRUE > is.numeric(a) [1] FALSE Actually, the way I initialize a list of known length is by

Hi, there: I spent some time on this but I think I really cannot figure it out, maybe I missed something here: my data looks like this: > dim(trn3) [1] 7361 209 > dim(val3) [1] 7427 209 > mg.rf2<-randomForest(x=trn3[,1:208], y=trn3[,209], data=trn3, xtest=val3[, 1:208], ytest=val3[,209], importance=T) my test data has 7427 observations but after prediction, > dim(mg.rf2$votes)

Hi, I have a dataset and want to build a generalized linear model on it. Unfortunately, complete.cases(df) returns null, which means I have to find a way to "fill" those missings. One way is following my previous post to use median to replace(or use most freq. of level to replace for catergorical case), but I am wondering if there are other ways, when glm or something like it is

Hi, I have a question on write.table: I have a data.frame called t7 as below: > dim(t7) [1] 14015184 6 > t7[1:5,] uci uce par line graphical.forms stems 1 0 0 0 0 active activ 2 0 0 0 0 policy polici 3 0 0 0 0 wc PC 4 0 0 0 0 eff elf 5 0 0 0 0 icn ICC I want to write the

Hi, there: I am wondering if there is a quick way to "reverse" a list like this: t0 <- list(a=1, b=1, c=2, d=1) reverst t0 to t1 > t1 $`1` [1] "a" "b" "d" $`2` [1] "c" thanks. -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Hi, I searched the archives and did not find a good solution to that. assume I have 10 sets and I want to have the common character elements of them. how could i do that? -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

http://www.nabble.com/file/p24569511/mahalanobis.txt mahalanobis.txt http://www.nabble.com/file/p24569511/concentrations.txt concentrations.txt Dear Forum members, I have a problem calculating mahalanobis distances. My data file mahalanobis.txt and categories file concentrations.txt are attached. I do the following steps: x <- as.matrix(read.table("mahalanobis.txt", header=TRUE))

Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? 2) clustering is the clusters vector as result of one of the many clustering methods?

Hi, I am wondering how to make a function Fun to make the following work: t0 <- (paste("hgu133a", "ENTREZID", sep="")) xx <- as.list(Fun(t0)) # make it work like xx<-as.list(hgu133aENTREZID) thanks, -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Hi, forgive me if it is due to my "laziness" :) I am wondering if there are functionalities in R, which can do like "more" and "tab" in linux: more(one.data.frame) so I can browse through it. Sometimes I can use one.data.frame[1:100,], but still not as good as "more" in linux. tab: can I use tab to auto complete an defined object name in R so I don't

Hi, there: I am wondering if anyone here can provide an example using pca doing dimension reduction for a dataset. The dataset can be n*q (n>=q or n<=q). As to dimension reduction, are there other implementations for like ICA, Isomap, Locally Linear Embedding... Thanks, weiwei -- Weiwei Shi, Ph.D "Did you always know?" "No, I did not. But I believed..." ---Matrix III