search for: klar

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Nu...

...gression/classification models and in cases where we have only one input variable NaiveBayes throws an error. Maybe I am mistaken and I shouldn't expect to have a model with only one input variable. We use R version 2.6.0 (2007-10-03). We use caret (v4.1.19), but have tested similar code with klaR (v.0.5.8), because caret relies on NaiveBayes implementation from klaR. I get different error messages from caret than from klaR so I will provide the code for caret usage and klaR usage. Here is the code which uses the iris dataset. > library(klaR); Loading required package: MASS > X<-i...

Hi ! Right now I am learning to use svm functions available in R and trying to use these function with given example. I was stuck with svmlight function which is available in klaR package. Any help would be appreciated regarding this function. 1. I am unable to use svmlight( ) which is available in package: klaR. Although I have downloaded klaR_0.6-3 package from http://cran.r-project.org/web/packages/klaR/index.html web site, the function is giving me the following error....

Dear all, I have a question on the shardsplot package:klaR(see the below Example). Plese tell me the meanings of " logstand <- t((t(logcount) / sdlogcount) * c(1,2,6,5,5,3))", much more. Why does this example use "c(1,2,6,5,5,3)" ? Examples: # Compute clusters and an Eight Directions Arranged Map for the # country d...

Dear all, I am trying to do a n-fold cross-validation for a regularized discrimant function analysis using rda from the package klaR. However, I have problems to predict the groups from the test/validation sample. The exmaples of the R documantation and some online webpage also do not work. Does anybody know what I have done wrong? Here my code # I want to use the first 6 observations for validationg the model, case 7 to 36 ar...

Sorry, I forgot to mention that I used the package "klaR". > > Dear all, I am trying to do a n-fold cross-validation for a > regularized discrimant function analysis using rda from the package > klaR. However, I have problems to predict the groups from the > test/validation sample. The exmaples of the R documantation and &gt...

I use Windows, R version 2.5.1 When I try to run stepclass (klaR) I get an error message/warning saying: 1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, ... Actually, I look 16 warnings of this type. Can anyone tell me what this means? Also, it returns only 2 out of the 79 variables as importan...

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true? another possibility is that "lda" (from MASS) computes CV classification rates from a random subsample instead of using all the data (?) That might be a sensible choice with a very...

Hi, I'm trying to use "stepclass" to do a stepwise variable selection with method=lda. I keep getting this warning message, which shows up once for each variable added to the model during variable selection: Warning message: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, I don't know how to interpret this warning. I

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend = levels(iris[, 5]),pch = 16, horiz = TRUE) par(opar) ---------------- Ebi [[altern...

...uld also like to make stepclass work with knn but knn does not have a 'predict' method, which is a requirement for a classification method to work with stepclass. Is there any way to get around this? Thanks, Soma library("e1071") library("randomForest") library("klaR") td <- read.table("dgdata1.txt", header=TRUE, sep=",") dgenes <- subset(td, dg == 1, select = dg:eg) ndgenes <- subset(td, dg == 0, select = dg:eg) n1 <- nrow(dgenes) n2 <- nrow(ndgenes) ndgrows <- 1:n2 selrows <- sample(ndgrows) sndgenes <- ndgene...

...rning messages: 1: svm_learn not found 2: cannot open file '_model_1.txt' > myData[1:2,] y X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 1 1 63 1 0 0 145 233 1 1 0 150 0 2.3 1 0 0 1 0 2 0 67 0 1 0 160 286 0 1 0 108 1 1.5 0 1 3 0 1 The klaR version is 0.4-1 OS: trying on windows and Linux gives me the same error -Luke

Hi I want to create a nice picture about my result of k -the nearest neighbours algorithm. Here is my easy code: ################################# library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F) KNN=ipredknn(diabetes~glucose+insulin,data=dane,subset=zbior.uczacy,k=3) KNN=ipredknn(diab...

...if there is a "predict"-function for glmms in R? Because I would like to produce a predictive habitat-map (someone asked that before, but I think there was no answer so far). And the third, why the method "laplace" doesn't work with all my models. thank you very much nina klar R output for a model, which works with laplace: > model4a<-lmer(RESPONSE~ D_TO_FORAL + + I((DIST_WATER-200)*(DIST_WATER<200)) + + I((DIST_VILL-900)*(DIST_VILL<900)) + + (1|TIER), family=binomial, method="Laplace") > summary(model4a) Generalized linear mixed model fit u...

On Fri, May 14, 2010 at 09:10:57PM +0200, Peter Klar wrote: > As the bug seems to be related to the SLAB allocator, the dump says ''kernel > BUG at mm/slub.c:2969!'', I also recompiled the kernel using the SLAB instead > of SLUB allocator, but this does not make any difference, the behaviour is > the same (beside the du...

On Fri, May 14, 2010 at 09:10:57PM +0200, Peter Klar wrote: > As the bug seems to be related to the SLAB allocator, the dump says ''kernel > BUG at mm/slub.c:2969!'', I also recompiled the kernel using the SLAB instead > of SLUB allocator, but this does not make any difference, the behaviour is > the same (beside the du...

Hi, Currently I testing the packets that contain built-in features for classification. Actually I looked packages such as: e1071, Klar, Caret, CORElearn. However, from what I noticed when building a naive Bayesian classifier, that they package use of the finite mixture model to estimate P (x | C) and using a normal distribution. In my research I use binary data and I want modeled P (x | C), eg the Poisson distribution. Are the pac...

Hello, I used the lda function from the MASS (VR) package and the rda function from the klaR package. I wanted to compare the result of this two functions by using the same training set. Thus, I used the rda function with lambda=1 an gamma=0, I should emulate the lda function and I should obtain the same result. But this it not the case, the two result are very different. My training s...

...89 4 Cr 100 I've worked up a trivial example below. Can anyone offer any suggestions on how I might go about doing this in R? I am working in a MAC OS environment with a current version of R. Many thanks in advance! Tyler #Example library(scatterplot3d) library(klaR) Al <-runif(27, 0, 125) QRBdfa <- as.data.frame(Al) QRBdfa$LANDUSE <- factor(c("A","A","A","B","B","B","C","C","C")) QRBdfa$Sb <- runif(27, 0, 1) QRBdfa$Ba <- runif(27, 0, 235) QRBdfa$Bi <-...

Hi everybody! I want to find a closer neighbourins observation. This is my code: ########################## library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F) klasyfikatorKNN=ipredknn(diabetes~glucose+insulin,data=dane,subset=zbior.uczacy,k=3) oceny...