[R] Defining Variables from a Matrix for 10-Fold Cross Validation

[David Winsemius]

> On Oct 9, 2018, at 3:04 PM, matthew campbell <mcc3qb using 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