search for: xiaoliu

Displaying 6 results from an estimated 6 matches for "xiaoliu".

2011 May 12
2
Can ROC be used as a metric for optimal model selection for randomForest?
...train.default(x = trainPred, y = trainDep, method = "rf", : The metric "ROC" was not in the result set. Accuracy will be used instead." I wonder if ROC metric can be used for randomForest? Have I missed something? Very very grateful if anyone can help! Best regards, XiaoLiu [[alternative HTML version deleted]]
2004 Mar 11
5
Receiver Operator Characteristic curve
Dear R-helpers: I want to calculate area under a Receiver Operator Characteristic curve. Where can I find related functions? Thank you in advance Xiao
2005 Apr 27
1
R/Splus--Perl Interface && ssh
...ib setenv R_HOME /usr/lib/R perl -I/usr/lib/R/site-library/RSPerl/examples/../share/blib/arch -I/usr/lib/R/site-library/RSPerl/examples/../share/blib/lib -I/usr/lib/R/site-library/RSPerl/scripts t t.pl I used ssh to submit my job to machine 'queen' ssh queen 'cd /nfs/fs/clarke/xiaoliu && ./doRSPerltt' An error message returns Fatal error: you must specify `--save', `--no-save' or `--vanilla' If using 'qsub' to submit my job to a GNQS system qsub doRSPerltt An error message returns Warning: no access to tty (Bad file descriptor). Th...
2004 Apr 11
1
Killed
I tried bootstrap on a sample of 13,000 observations: It works fine when R = 200: >boot(data, cor.i, R = 200) However, when R = 400, I got: >boot(data, cor.i, R = 400) Killed Any suggestions/ideas? Thank you very much Xiao
2004 Dec 17
1
package.skeleton()
Hi, R people: I generated a package using package.skeleton(). But I can not load it using library(). > package.skeleton("RDIPcor", list = c("ROCAUC.i", "cor.i"), path = "/home/xiao") Creating directories ... Creating DESCRIPTION ... Creating READMEs ... Saving functions and data ... Making help files ... Done. Further steps are described in
2004 Apr 10
1
confidential interval of correlation coefficient using bootstrap
I tried 2 methods to estimate C.I. of correlation coefficient of variables x and y: > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) #METHOD 1: Pearson's ********************************************************** > cor.test(x, y, method = "pearson", conf.level = 0.95) Pearson's