## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(GRNNs) ## ----------------------------------------------------------------------------- data("met") data("physg") ## ----eval = FALSE------------------------------------------------------------- # data("met") # data("physg") # results_kfold<-grnn.kfold(physg,met,10,"euclidean",scale=TRUE) ## ----eval = FALSE------------------------------------------------------------- # data("met") # data("physg") # best.spread<-findSpread(physg,met,10,"bray",scale=TRUE) ## ----------------------------------------------------------------------------- data("met") data("physg") best.spread<-c(0.33,0.33,0.31,0.34,0.35,0.35,0.32,0.31,0.29,0.35,0.35) predict<-physg[1,] physg.train<-physg[-1,] met.train<-met[-1,] prediction<-grnn(predict,physg.train,met.train,fun="euclidean",best.spread,scale=TRUE) ## ----------------------------------------------------------------------------- data("physg") physg.train<-physg[1:10,] physg.test<-physg[11:30,] distance<-grnn.distance(physg.test,physg.train,"bray")