similar to: GA/SWARM Hyperparameter (HP) Optimisation for Classification based Machine Learning

Hi, I'm currently fiddling with Docker Swarm on three sandbox servers running CentOS 7. Unfortunately I couldn't get even the most basic configuration running. After some experimenting and investigating, it turns out there's a problem with FirewallD. Here's what I did first on every single node. # firewall-cmd --permanent --add-service=docker-swarm # firewall-cmd --reload I

Hello, Everyone. For those, who saw crazy videos from code swarm (http://vis.cs.ucdavis.edu/~ogawa/codeswarm/) and asked 'what's about LLVM' I've created two videos: 1. clang: http://vimeo.com/1242653 2. LLVM itself: http://vimeo.com/1246374 Enjoy! If anybody wants 'sources' for recreation of these videos (e.g. changing settings, etc) - just drop e-mail to me. -- With

Dear Sir, I would like to contribute Rancher / Docker Swarm on CentOS and related WIKI. Please advise what do I need to for this WIKI. Thank you! Xlord -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos-docs/attachments/20170704/c197bbc3/attachment.html>

Oh yeah! I''m working on a web interface to manage virtualization tecnologies like xen, kvm and lguest using libvirt connection. I need help! How i can code something like swarm (see azureus bittorrent client screenshots to understand) ? -- Regards, Luiz Vitor Vitor Martinez Cardoso. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are

Hi all, installed the old space shooter Swarm and it is running fine pleased to say except artefacts of lasers and rockets that have been fired staying on screen for up to another 6 seconds. This is as you can imagine a bit irritating as they move with and stay on the screen. Wine x.19. Have set the game to 'unmanaged' by the window manager as was suggested here in another thread, but

Hi I planned to learn R and their machine learning algorithms such as xgboost. I just installed R 3.3 in our CentOS linux system. Linus system: centos-release-6-9.el6.12.3.x86_64 I used the command: yum install R. I successfully install "rJava" and "mlr" packages. Then I used the following command: install.packages("xgboost") Unfortunately, I cannot install xgboost

Hi All, I tried to use xgboost to model and predict count data. The predictions are however not as expected as shown below. # sponge count data in library(spm) library(spm) data(sponge) data(sponge.grid) names(sponge) [1] "easting" "northing" "sponge" "tpi3" "var7" "entro7" "bs34" "bs11"

> On Oct 20, 2017, at 11:11 AM, C W <tmrsg11 at gmail.com> wrote: > > Dear R list, > > I came across dgCMatrix. I believe this class is associated with sparse > matrix. Yes. See: help('dgCMatrix-class', pack=Matrix) If Martin Maechler happens to respond to this you should listen to him rather than anything I write. Much of what the Matrix package does appears

Subsetting using [] vs. head(), gives different results. R code: > head(train$data, 5) [1] 0 0 1 0 0 > train$data[1:5, 1:5] 5 x 5 sparse Matrix of class "dgCMatrix" cap-shape=bell cap-shape=conical cap-shape=convex [1,] . . 1 [2,] . . 1 [3,] 1 .

Dear R list, I came across dgCMatrix. I believe this class is associated with sparse matrix. I see there are 8 attributes to train$data, I am confused why are there so many, some are vectors, what do they do? Here's the R code: library(xgboost) data(agaricus.train, package='xgboost') data(agaricus.test, package='xgboost') train <- agaricus.train test <- agaricus.test

>>>>> C W <tmrsg11 at gmail.com> >>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > Thank you for your responses. I guess I don't feel > alone. I don't find the documentation go into any detail. > I also find it surprising that, >> object.size(train$data) > 1730904 bytes >>

> On Oct 21, 2017, at 7:50 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > >>>>>> C W <tmrsg11 at gmail.com> >>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > >> Thank you for your responses. I guess I don't feel >> alone. I don't find the documentation go into any detail. > >> I also find

Dear everybody: HDF5, a dataset formatting library, and R that is built with it, have been uploaded to ftp://ftp-fis.iarc.fr/pub/incoming. The R RPM uses the spec file created by Martyn Plummer as a starting point, and makes only a few trivial changes. -rw-rw-r-- 1 ftp 100 3416612 Oct 6 17:45 R-base-with-hdf5-0.65.1-1.i386.rpm -rw-rw-r-- 1 ftp 100 2300453 Oct 6 17:48

HDF5 is a high quality data storage format from NCSA (http://hdf.ncsa.uiuc.edu/index.html) Marcus Daniels of the Swarm Development Group has made available an R library called hdf5 which allows loading and saving of data in hdf5 format. The source for his library is here: ftp://ftp.swarm.org/pub/swarm/src/testing/hdf5_1.4.7.tar.gz I prefer to use RPMs to maintain software across many linux

Thank you for your responses. I guess I don't feel alone. I don't find the documentation go into any detail. I also find it surprising that, > object.size(train$data) 1730904 bytes > object.size(as.matrix(train$data)) 6575016 bytes the dgCMatrix actually takes less memory, though it *looks* like the opposite. Cheers! On Fri, Oct 20, 2017 at 3:22 PM, David Winsemius

Dear R and hydrological/environmental community, A major release of hydroPSO is now available on CRAN. This new release: -) implements the Standard Particle Swarm 2011 (SPSO-2011) -) is parallel-capable, to alleviate the computational burden of complex models with "long" execution time -) has an improved performance (33% - 38% faster) -) allows normalization, when the parameter space

Dear R and hydrological/environmental community, A major release of hydroPSO is now available on CRAN. This new release: -) implements the Standard Particle Swarm 2011 (SPSO-2011) -) is parallel-capable, to alleviate the computational burden of complex models with "long" execution time -) has an improved performance (33% - 38% faster) -) allows normalization, when the parameter space

Estimados amigos: Esta tarde he estado probando la librería mlr3, que me resulta muy interesante para trabajos de clasificación. En concreto, para entender su funcionamiento he probado un ejemplo simple (viene en CRAN). Sin embargo, cuando cambio el parámetro de clasifiación en la función de aprendizaje, me aparece el error siguiente: *Error: Element with key

Estimadísimo Carlos: Muchísimas gracias por responderme y hacerlo tan rápido. Contemplé esa posibilidad, es decir, que el hiperparámetro estuviera suponiendo un problema, y probé de esta forma: > learner <- lrn("classif.ranger", num.trees = 5, mtry = NULL) Error: Element with key 'classif.ranger' not found in DictionaryLearner!

Since 2008, Microsoft (formerly Revolution Analytics) staff and guests have written about R every weekday at the Revolutions blog (http://blog.revolutionanalytics.com) and every month I post a summary of articles from the previous month of particular interest to readers of r-help. In case you missed them, here are some articles related to R from the month of July: A tutorial on using the