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Cross Validation

Discussion in 'Education' started by mattyice33x, Oct 8, 2018.

  1. mattyice33x

    mattyice33x Guest

    I am working on a 10-fold cross validation problem, and am having an issue with part of my code. Specifically, I'm having a problem with my "for (1 in nfold)" argument, and with the variable length of x. Is there a better way to set up cross-validation than this? Also, I'm not familiar with the last error message regarding the variable length of x--what exactly does this mean, and how might I correct it?

    I've attached my code (the data set is included in the ElemStatLearn package).

    Any help is appreciated, Thanks!





    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)))

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

    mydata = data.frame(x = train[,c(-1,-4)] , y = train[,1])

    K = 20

    errorMatrix = matrix(NA, K, 10) for (1 in nfold)

    Error: unexpected numeric constant in "for (1"

    { + 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')

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