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Dear R-philes: I am having an issue with exporting contingency tables with xtable(). I set up a contingency and convert it to a matrix for passing to xtable() as shown below. v.cont.table <- table(v_lda$class, grps, dnn=c("predicted", "observed")) v.cont.mat <- as.matrix(v.cont.table) Both produce output as follows: observed predicted uh uh~ uh 201

Hello Everyone, Let's say I have a vector as follows: vowels = c("aa", "aa", "ah", "ao", "eh) I want to make a factor consisting of two levels: the things that are "aa" and those that are not "aa". How would I do that? I tried using factor(vowels, levels=c("aa", "~aa"), exclude=NULL), but this gives

R-philes, I have a question about displaying counts of unused factors using the table() function. I have two vectors with character data in them: local.labels("ah", "ah", "ah~") local.preds("ah", "ah", "ah") If I use the table function as shown below, I get an error because the number of levels do not match up. v.cont.table <-

Hello R-philes: I have the following function that gets the output of mget() and converts it to a data frame to return. What I am finding is that the dimensions are wrong. Basically, I get: bridesmaid wed u see m gt lt like love X.0 dress pagetrack one go X3 get 1 56 35 27 30 24 20 20 23 28 17 25 16 16 28 15 26 Instead, I want something like: [1] bridesmaid

Dear R-philes, I am having some trouble averaging across multiple runs of a classifier in an ROC Curve. I am using the ROCR package and the plot() method. First, I initialize a list with two elements where each element is a list of predictions and labels: vowel.ROC <- list(predictions=list(), labels=list()) For every run of the classifier, I append the scores and labels to their

Dear R-philes, I am plotting ROC curves for several cross-validation runs of a classifier (using the function below). In addition to the average AUC, I am interested in obtaining a confidence interval for the average AUC. Is there a straightforward way to do this via the ROCR package? plot_roc_curve <- function(roc.dat, plt.title) { #print(str(vowel.ROC)) pred <-