search for: iris1

...t - even though there are no occurences. Where does it get the values versicolor and virginica from and give then a count of 0? What am I missing? Thanks in advance. > summary(iris$Species) setosa versicolor virginica 50 50 50 > nrow(iris) [1] 150 > iris1 <- iris[iris$Species == 'setosa',] > nrow(iris1) [1] 50 > summary(iris1$Species) setosa versicolor virginica 50 0 0 boxplot(Petal.Width ~ Species, data = iris1, plot=1) > iris2 <- subset(iris, Species == 'setosa') > nrow(iris2)...

I require some help in debugging this code  library(neuralnet) ir<-read.table(file="iris_data.txt",header=TRUE,row.names=NULL) ir1 <- data.frame(ir[1:100,2:6]) ir2 <- data.frame(ifelse(ir1$Species=="setosa",1,ifelse(ir1$Species=="versicolor",0,""))) colnames(ir2)<-("Output") ir3 <- data.frame(rbind(ir1[1:4],ir2))

Hello, I'm trying to pull data from a network drive on a windows machine. The location is read into a string <rem> and then used later with a data input command. > rem<- "\\192.192.192.3\Shared\iris1.csv" Warning messages: 1: '\S' is an unrecognized escape in a character string 2: '\i' is an unrecognized escape in a character string 3: unrecognized escapes removed from "\\192.168.16.3\Shared\iris1.csv" When using a data input operation datafile<- read.csv(rem...

Dear R-help, This is about randomForest's handling of NA and NaNs in test set data. Currently, if the test set data contains an NA or NaN then predict.randomForest will skip that row in the output. I would like to change that behavior to outputting an NA. Can this be done with flags to randomForest? If not can some sort of wrapper be built to put the NAs back in? thanks, Clayton

I'm trying to select a subset of a dataframe while dropping some factors. While the dataset gets smaller all Factor levels remain and I need to get rid of them. Strangely enough, I am almost certain that the same code on the same data worked OK earlier today - and it is not the first time that I'm not able to replicate earlier results with this command (I know, I might just be going

Hello List, I am looking for efficient code to produce the Cartesian product of two or more data.frames. I'd like to be able to do this without resorting to looping. I have searched the FAQ, web, etc without luck. That being said, the help page for merge says that the function can produce what I'm looking for if the by vectors are of zero length. Would someone be so kind as to