similar to: lda (MASS)

Good afternoon. I would like to know if there is any function in R to do LOOCV with these classifiers: 1)SVM 2)Neural Networks 3)C4.5 ( J48) 4)KNN Thanks a lot! [[alternative HTML version deleted]]

Hi this is my first post. I am trying to run a simulation for a computer playing Von Neumann poker and adjusting it's expectation of an opponent's behavior according to how the opponent plays. This program involves random generation of "hands" and shifting of parameters. However, when I run the code, no errors come up, but the program doesn't do anything. Could someone

Using R 2.0.0 of July 20 2004 train, test, and cl as defined in example(knn), we have > search() [1] ".GlobalEnv" "package:methods" "package:stats" "package:graphics" [5] "package:utils" "Autoloads" "package:base" > knn(train, test, cl, k=3) Error: couldn't find function "knn" >

Hello. I found the behavior of knn( http://stat.ethz.ch/R-manual/R-devel/library/class/html/knn.html) function looking very strange. Consider the toy example. > library(class) > train <- matrix(nrow=5000,ncol=2,data=rnorm(10000,0,1)) > test <- matrix(nrow=10,ncol=2,data=rnorm(20,0,1)) > cl <- rep(c(0,1),2500) > knn(train,test,cl,1) [1] 1 1 0 0 1 0 1 1 0 1 Levels: 0 1 It

Depending on the setting of par()$usr, the 'at' setting in mtext(.., adj=0, outer=T) may cause the text to appear in an anomalous position (e. g. in the first instance below, at the left of the plot region rather than at 'at=0' in the figure region), or the text may not appear at all. If one does not set the 'at' parameter the text appears (with 'adj=0') on the

Hi, I was trying to get the optimal 'k' for the knn. To do this I was using the following function : knn.cvk <- function(datmat, cl, k = 2:9) { datmatT <- (datmat) cv.err <- cl.pred <- c() for (i in k) { newpre <- as.vector(knn.cv(datmatT, cl, k = i)) cl.pred <- cbind(cl.pred, newpre) cv.err <- c(cv.err, sum(cl != newpre)) }

Dear R community, I've been writing simple functions for the past year and half and have come across a similar problem several times. The execution of a function within my own function produces NaN's or fails to execute as intended. My conundrum is that I can execute the function outside of my function without error, so it's difficult for me, as a novice functioneer, to figure out

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)

hi I'm learning R and making some examples. One of them is that for given distribution I show density function, distribution function expected value and variance(?). I know EX <- function(xval,xprob) sum( (xval*xprob) ); where xval is vector of values and xprob vector of probabalities, but DX <- function(xval,xprob) EX((xval^2),xprob) - (EX(xval,xprob))^2; doesn't work as I

Hello, I am feeling that this question can have a very simple answer, but I can't find it. I need to use the function knn.dist from knnflex library. Whatever I try, I get the error: Error in as.vector.dist(x, "character") : unused argument(s) ("character") First example: > a<-NULL > a<-rbind(a,c(5.2,-8.1)) > a<-rbind(a,c(8.8,-16.1)) >

Dear R users, I'm working with the rpart package and want to evaluate the performance of user defined split functions. I have some problems in understanding the meaning of the xval argument in the two functions rpart.control and xpred.rpart. In the former it is defined as the number of cross-validations while in the latter it is defined as the number of cross-validation groups. If I am

Maybe you should show your colleague how to access help pages in R? Right in ?knn, it says: prob: If this is true, the proportion of the votes for the winning class are returned as attribute 'prob'. so 1.0 mean all three NNs are of the `winning'; i.e., predicted, class, and 0.66667 means 2 out of the 3 NNs are of the winning class, etc. Andy > From: Ko-Kang

New major versions of the caret packages (caret 3.37, caretLSF 1.23 and caretNWS 0.23) have been uploaded to CRAN. caret is a package for building and evaluating a wide variety of predictive models. There are functions for pre-processing, tuning models using resampling, visualizing the results, calculating performance and estimating variable importance. caretNWS and caretLSF are two parallel

New major versions of the caret packages (caret 3.37, caretLSF 1.23 and caretNWS 0.23) have been uploaded to CRAN. caret is a package for building and evaluating a wide variety of predictive models. There are functions for pre-processing, tuning models using resampling, visualizing the results, calculating performance and estimating variable importance. caretNWS and caretLSF are two parallel

Dear R-help and ROCR developers (Tobias Sing and Oliver Sander) - I think my first question is generic and could apply to many methods, which is why I'm directing this initially to R-help as well as Tobias and Oliver. Question 1. The plot function in ROCR will average your cross validation data if asked. I'd like to use that averaged data to find a "best" cutoff but I

Dear R's I'm trying to use specific rather than random cross-validation groups in mvpart. The man page says: xval Number of cross-validations or vector defining cross-validation groups. And I found this reply to the list by Terry Therneau from 2006 The rpart function allows one to give the cross-validation groups explicitly. So if the number of observations was 10, you could use

I am trying to use knn to do a nearest neighbor classification. I tried using my dataset and got an error message so I used a simple example to try and understand what I was doing wrong and got the same message. Here is what I typed into R: try [,1] [,2] [,3] [,4] r "A" "A" "T" "G" r "A" "A" "T" "G" f

ear all, This is my first time using this listserv and I am seeking help from the expert. OK, here is my question, I am trying to use impute.knn function in impute library and when I tested the sample code, I got the error as followingt: Here is the sample code: library(impute) data(khanmiss) khan.expr <- khanmiss[-1, -(1:2)] ## ## First example ## if(exists(".Random.seed"))

Dear List, I have a question regarding "ipred" package. Under 10-fold cv, for different knn ( = 1,3,...25), I am getting same misclassification errors: ############################################# library(ipred) data(iris) cv.k = 10 ## 10-fold cross-validation bwpredict.knn <- function(object, newdata) predict.ipredknn(object, newdata, type="class") for (i in

The function knn.cv in the class package doesn't have error checking to ensure that the length of the classlabel argument is equal to the number of rows in the test set. If the classlabel is short, the result is often a segfault. > library(class) > dat <- matrix(rnorm(1000), nrow=10) > cl <- c(rep(1,5), rep(2,5)) > cl2 <- c(rep(1,5), rep(2,4)) > knn.cv(dat, cl) [1] 2