Hi all
I receive this error message: Error in mymodel$MSE : $ operator is invalid
for atomic vectors
When I use KNN.
This is the code:
library(e1071)
train <- rbind(iris3[,,1], iris3[,,2], iris3[,,3])
cl <- factor(c(rep("s",50), rep("c",50), rep("v",50)))
knn.cv(train, cl, k = 3, prob
e
> To: nancyada...@hotmail.com
> CC: r-help@r-project.org
> Subject: Re: [R] Error with KNN
>
>
>
> On 20.02.2010 19:10, Nancy Adam wrote:
> >
> >
> >
> > Hi all
> >
> > I receive this error message: Error in mymodel$MSE : $ operator is inval
Hi,
Could you please help me in solving the following error message:
Error in `[.data.frame`(mytestdata, fp_temp == 1) :
undefined columns selected
when I use scan instead on read.table, I reicieve this message:
Error in names(ret2) <- rowns :
'names' attribute [172] must be the same
Hi all,
Could you please help me in solving the following error message:
Error in `[.data.frame`(mytestdata, fp_temp == 1) :
undefined columns selected
when I use scan instead on read.table, I reicieve this message:
Error in names(ret2) <- rowns :
'names' attribute [172] must be the same
colon.
> Try
>
> train = read.csv('trainingset.txt',check.names=FALSE)
> test = read.csv('testset.txt',check.names=FALSE)
>
> - Phil Spector
> Statistical Computing Facility
> Department of Statistics
> UC Berkeley
> spec...@stat.berkeley.edu
>
>
Hi all,
Thanks for the explanation
I got other datasets that are already used with others but I got the same
errors:
“undefined columns selected”
I attach the datasets with this email and this is the command I’m trying:
train = read.csv("trainingset.txt",check.names=FALSE)
test = read.csv("test
Hi all,
I tried many things to read any dataset but I receive different error messages
every time.
One new message is: vector size specified is too large
Can any one please send any part from any dataset just for testing a regression
system and to know where is the problem??
Many thanks,
N
Hi everyone,
Can anyone please tell whether there is a difference between the code for using
svm in regression and code for using svm in classification?
This is my code for regression, should I change it to do classification?:
train <- read.table("trainingset.txt",sep=";")
test <- read.
Hi everyone,
I tried to write the code of computing R2 for a regression system but I failed.
This is the code I use for computing RMSE:
my_svm_model <- function(myformula, mydata, mytestdata)
{
mymodel <- svm(myformula, data=mydata)
mytest <- predict(mymodel, mytestdata
Dec 2009 10:36:36 -0500
> Subject: Re: [R] svm regression/classification
> From: mailinglist.honey...@gmail.com
> To: nancyada...@hotmail.com
> CC: r-help@r-project.org
>
> Hi Nancy,
>
> Comments in line:
>
> On Sun, Dec 27, 2009 at 3:34 AM, Nancy Adam wrote:
>
ecatedʼ but is not actually
> mentioned on that page. Even though it has been deprecated in S
> for 20 years, it is still accepted.
>
> I added that note in May 2008 (and it is not intended to be a
> reference to current versions of S-PLUS, since we cannot keep checking
> that,
> > for many years. It appears as an index entry in Becker _et al_
> > (1988), pointing to the help for ʽDeprecatedʼ but is not actually
> > mentioned on that page. Even though it has been deprecated in S
> > for 20 years, it is still accepted.
> >
> > I added that not
Hi everyone,
Can someone please help me in these questions?:
1)if I use crossvalidation with svm, do I have to use this equation to
calculate RMSE?:
mymodel <- svm(myformula,data=mydata,cross=10)
sqrt(mean(mymodel$MSE))
But if I dont use crossvalidation, I have to use the foll
odel will use only the
last column on the testing set?Many thanks,Nancy
> Date: Sat, 2 Jan 2010 17:32:44 -0500
> Subject: Re: [R] Questions bout SVM
> From: mailinglist.honey...@gmail.com
> To: nancyada...@hotmail.com
> CC: r-help@r-project.org
>
> Hi,
>
> On Fri
hi all,
Im trying to install e1071 package to a new computer but I failed. Can any one
please tell me how I download it without installing through R? can anyone
please send it as an attachment please?
Many thanks,
Nancy
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