Update xgb.cv.R
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@ -216,7 +216,11 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
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if (prediction) {
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for (k in 1:nfold) {
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fd = xgb_folds[[k]]
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res = xgb.iter.eval(fd$booster, fd$watchlist, i - 1, feval, prediction)
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if (!is.null(early.stop.round) && earlyStopflag) {
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res = xgb.iter.eval(fd$booster, fd$watchlist, bestInd - 1, feval, prediction)
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} else {
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res = xgb.iter.eval(fd$booster, fd$watchlist, nrounds - 1, feval, prediction)
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}
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if (mat_pred) {
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pred_mat = matrix(res[[2]],num_class,length(fd$index))
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predictValues[fd$index,] = t(pred_mat)
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