all'
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] X-fold cross validation function for discriminant analysis
One option is the Bioconductor package MLInterfaces that provides a unified
interface for several machine learning alrogirithms and methods for
cross-validation etc. See the algorithms
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-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Wensui Liu
Sent: Thursday, November 16, 2006 11:37 AM
To: Wade Wall
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] X-fold cross validation function
Hi, Wade:
Some functions in R have n-fold cv themselves. For example, if you are
looking for a linear discriminant analysis (lda {MASS}), it comes with
a "leave-one-out" cv in which n equals the size of training sample,
and it gives you pretty good estimation of error rate. But be advised,
this est
how hard is it to write one though?
On 11/16/06, Wade Wall <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> I ran a discriminant analysis with some data and want to get a general idea
> of prediction error rate. Some have suggested using X-fold cross validation
> procedure. Anyone know if there is a fun
Hi all,
I ran a discriminant analysis with some data and want to get a general idea
of prediction error rate. Some have suggested using X-fold cross validation
procedure. Anyone know if there is a function for this in R?
Thanks,
Wade
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