I think we are having some difficulty understanding what you are looking for. If you are looking to find which of the training samples were closest to the prediction sample, I don't think that you can get it from this function.
If this is what you want, I use the dist function in the proxy package. Max On Tue, Oct 27, 2009 at 8:46 AM, David Winsemius <dwinsem...@comcast.net> wrote: > > On Oct 27, 2009, at 6:02 AM, Grzes wrote: > >> >> 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=predict(klasyfikatorKNN,dane[-zbior.uczacy,],"class") >> >> #data frames with my result from klasyfikatorKNN >> >> df=data.frame(glucose=c(klasyfikatorKNN$learn$X[,1]),insulin=klasyfikatorKNN$learn$X[,2],diabetes=c(klasyfikatorKNN$learn$y)) >> #And picture >> drawparti(as.factor(df$diabetes), df$glucose, df$insulin, method = "sknn", >> prec = 100, xlab = NULL, ylab = NULL) > > I get an error: Error: could not find function "drawparti" > >> >> ########################## >> My question is: How or where may I find correct or wrong values which >> were >> drawn (found,classification) in this picture? > > No picture resulted. > >> It means I'm looking for x, y >> values. > > Not sure exactly what you are asking. Does this modification to df and > fairly obvious the cross table help? > >> >> df=data.frame(glucose=c(klasyfikatorKNN$learn$X[,1]),insulin=klasyfikatorKNN$learn$X[,2],pred.diabetes=klasyfikatorKNN$learn$y, >> trueDiab=dane[,3]) > Warning message: > In data.frame(glucose = c(klasyfikatorKNN$learn$X[, 1]), insulin = > klasyfikatorKNN$learn$X[, : > row names were found from a short variable and have been discarded >> with( df, table(pred.diabetes, trueDiab)) > trueDiab > pred.diabetes neg pos > neg 174 86 > pos 88 44 > > > >> >> >> -- >> View this message in context: >> http://www.nabble.com/%22ipredknn%22---How-may-I-find-values--tp26074994p26074994.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > David Winsemius, MD > Heritage Laboratories > West Hartford, CT > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Max ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.