Defining Variables from a Matrix for 10-Fold Cross Validation

Message: 26
Date: Tue, 9 Oct 2018 15:34:15 -0700
From: David Winsemius <dwinsemius at comcast.net>
To: matthew campbell <mcc3qb at virginia.edu>
Cc: R-help at r-project.org
Subject: Re: [R]  Defining Variables from a Matrix for 10-Fold Cross
        Validation
Message-ID: <85DC895F-BEA2-4E47-ACC1-49A5C350B2D8 at comcast.net>
Content-Type: text/plain; charset="us-ascii"

On Oct 9, 2018, at 3:04 PM, matthew campbell <mcc3qb at virginia.edu> wrote:

Good afternoon,

I am trying to run a 10-fold CV, using a matrix as my data set.
Essentially, I want "y" to be the first column of the matrix, and my "x" to
be all remaining columns (2-257). I've posted some of the code I used
below, and the data set (called "zip.train") is in the "ElemStatLearn"
package. The error message is highlighted in red, and the corresponding
section of code is bolded. (I am not concerned with the warning message,
just the error message).

The issue I am experiencing is the error message below the code: I haven't
come across that specific message before, and am not exactly sure how to
interpret its meaning. What exactly is this error message trying to tell
me?  Any suggestions or insights are appreciated!

Thank you all,

Matthew Campbell

library (ElemStatLearn)
library(kknn)
data(zip.train)
train=zip.train[which(zip.train[,1] %in% c(2,3)),]
test=zip.test[which(zip.test[,1] %in% c(2,3)),]
nfold = 10
infold = sample(rep(1:10, length.out = (x)))

I don't see a definition for x.

Warning message:
In rep(1:10, length.out = (x)) :
 first element used of 'length.out' argument

But apparently it las a length greater than 1 and your are getting a sample whose length is specified by the first element of x.

*> mydata = data.frame(x = train[ , c(2,257)] , y = train[ , 1])*

K = 20
errorMatrix = matrix(NA, K, 10)

for (l in nfold)

+ {
+   for (k in 1:20)
+   {
+     knn.fit = kknn(y ~ x, train = mydata[infold != l, ], test =
mydata[infold == l, ], k = k)
+     errorMatrix[k, l] = mean((knn.fit$fitted.values - mydata$y[infold ==
l])^2)
+   }
+ }
Error in model.frame.default(formula, data = train) :
 variable lengths differ (found for 'x')

So the warning above is probably a great clue to the source of this error.

Morale of the tale: Always read the warnings, even if your code proceeds.

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David Winsemius
Alameda, CA, USA

"The whole problem with the world is that fools and fanatics are always so certain of themselves, and wiser people so full of doubts." - Bertrand Russell