search for: nrnodes

Hello. We''re currently using a Sun Blade1000 (2x750MHz, 1G ram, 2x160MB/s mpt scsi buses, skge GigE network) as a NFS backend with ZFS for distribution of free software like Debian (cdimage.debian.org, ftp.se.debian.org) and have run into some performance issues. We are running SX snv_48 and have run with a raidz2 with 7x300G for a while now, just added another 7x300G raidz2 today but

Greetings. I'm trying to determine whether to use rpart or randomForest for a classification tree. Has anybody tested efficacy formally? I've run both and the confusion matrix for rf beats rpart. I've looking at the rf help page and am unable to figure out how to extract the tree. But more than that I'm looking for a more comprehensive user's guide for randomForest including

...oportions of 0.44 and 0.56, respectively. In a call to the function randomForest() with mytry=1 and nodesize=1 and ntree=100 the resulting classifier puts all observations in class T. When I change nodesize to nodesize=5 I get the following error message: Error in array(rfout$treemap, dim = c(2, nrnodes, ntree)) : dim<- length of dims do not match the length of object Higher values of nodesize also result in this error message but values of nodesize less than 5 do not. I'm using R-1.5.0 on a Linux box and I installed the randomForest package during the week 13 May 2002. Thanks in advanc...

Hello, When I plot or look at the error rate vector for a random forest (rf$err.rate) it looks like a descending function except for a few first points of the vector with error rates values lower(sometimes much lower) than the general level of error rates for a forest with such number of trees when the error rates stop descending. Does it mean that there is a tree(s) (that is built the first in

This reimplements the augeas APIs using ocaml-augeas (dropping all the C code). The behaviour seems unchanged, although I may have not tested all the various corner cases. Changes from v2: - dropped patch #1, as it was applied already (was a real bugfix) - rebased on master Pino Toscano (3): Revert "Revert "daemon: implement OptString for OCaml APIs"" daemon: move augeas

This reimplements the augeas APIs using ocaml-augeas (dropping all the C code). The behaviour seems unchanged, although I may have not tested all the various corner cases. Pino Toscano (4): daemon: fix/enhance error reporting of Augeas exceptions Revert "Revert "daemon: implement OptString for OCaml APIs"" daemon: move augeas APIs to OCaml daemon: drop usage of C

This synchronizes the embedded ocaml-augeas copy, and reimplements the augeas APIs using it (dropping all the C code). The behaviour seems unchanged, although I may have not tested all the various corner cases. Pino Toscano (5): common/mlaugeas: Synchronize with latest ocaml-augeas daemon: fix/enhance error reporting of Augeas exceptions Revert "Revert "daemon: implement

...ot;root"); Int "flags"], []; tests = [ InitBasicFS, Always, TestResultString ( [["mkdir"; "/etc"]; @@ -99,7 +99,7 @@ Augeas functions." }; { defaults with name = "aug_defvar"; added = (0, 0, 7); - style = RInt "nrnodes", [String "name"; OptString "expr"], []; + style = RInt "nrnodes", [String (PlainString, "name"); OptString "expr"], []; shortdesc = "define an Augeas variable"; longdesc = "\ Defines an Augeas variable C<name&gt...

Very large but mechanical change to the generator. Rich.

This is a follow-up to the other generator changes in: https://www.redhat.com/archives/libguestfs/2017-February/msg00217.html Rich.

This started as a simple warning-elimination change. I'll get back to that series shortly ;-) It turned into a factorization and constification exercise during which I got a taste of ocaml. Thanks to Rich Jones for help with a few snippets in generator.ml. The overall result is that many previously-manually-maintained bits from daemon/*.c functions are now hoisted into the automatically-

Split up the huge generator/actions.ml into several smaller files. Rich.

The existing mechanism was clunky, slow and used ~ 10 MB of local disk. Rich.