revolution-r

RxXdfData, RxTextData, rxXdfToDataFrame

由 大城市里の小女人 提交于 2019-12-23 03:18:20
问题 I'm trying to find out what these functions do but I can't find much information on it and it is not very clear from what I have found out. can you help explain what they do? Thanks in advance 回答1: When you start out using Revo R or see demonstrations given, it's common to see functions being applied directly to a file path, like this: # Create a point to an insurance claims dataset installed with RRE xdfPath <- file.path(rxGetOption("sampleDataDir"), "claims.xdf") rxDataStep(xdfPath, numRows

Count distinct in a rxSummary

由 ◇◆丶佛笑我妖孽 提交于 2019-12-12 02:54:00
问题 I want to count distinct values of var2 grouping by var1 in a .xdf file, I tried something like this myFun <- function(dataList) { UniqueLevel <<- unique(c(UniqueLevel, dataList$var2)) SumUniqueLevel <<- length(UniqueLevel) return(NULL) } rxSummary(formula = ~ var1, data = "DefModelo2.xdf", transformFunc = myFun, transformObjects = list(UniqueLevel = NULL), removeZeroCounts = F) Thank you in advance EDIT: Probably using RevoPemaR is the the faster way 回答1: One other option is to use

How to only install versions of packages that were made under a specific R release?

由 ≡放荡痞女 提交于 2019-12-11 10:19:42
问题 I use the Revolution R Enterprise distribution that is built upon R 3.2.2. Hence, I have an interest in only employing package versions that are based on this R release as well. Checking packages like 'checkpoint' or the Revolution MRAN page, I only found ways to access snapshots of CRAN datewise. Is there a way to install the most recent package versions still compatible with a certain R release? 回答1: I found a heuristical solution to my own problem: Find out about the release date of the

Error: could not find function “rxGetOption” in Revolution R Open

由 女生的网名这么多〃 提交于 2019-12-10 22:27:07
问题 I downloaded and installed Revolution R Open. Current Version of R is 3.1.1 (2014-07-10) -- "Sock it to Me" and version of Revolution R Open is 8.0 beta. I have started basic tutorial from converting data to .xdf format(internal to Revolution). myTrainCsv <- file.path(rxGetOption("data"), "train.csv") However I receive a following error: Error in file.path(rxGetOption("data"), : could not find function "rxGetOption" It seems to me a newbie error. Anyway I can not find an answer just googling

lme() different results each run under Revolution R (MKL to blame?)

由 ￣綄美尐妖づ 提交于 2019-12-08 20:10:08
问题 Update (Aug 2014): I never got to the bottom of this, and never got any feedback on Revolution's forum. This issue, however, seems to have been fixed in Revolution R 7.2 (with R 3.0.3, again the academic version). I ran the lme() test below a few hundred times, all produced equal results, as expected.[ end of update ] I just installed the academic version of Revolution R 7.0 (R 3.0.2) on a new PC and am getting strange results for the code below. Every time the code is run, it gives different

R install package RevoScaleR

由 生来就可爱ヽ(ⅴ＜●) 提交于 2019-12-01 15:59:41
问题 In trying to install package "RevoScaleR", I get the following error. I have tried installing this package with various versions of R but get the same error every time. Does anyone have any idea why? install.packages("RevoScaleR") Warning in install.packages : package ‘RevoScaleR’ is not available (for R version 3.1.2) Any help is appreciated. 回答1: I am not sure what R version you are currently using but the latest stable version is 3.1.2. If the package installation warning is telling that

Error while using install_github | devtools | timeout issue

由 混江龙づ霸主 提交于 2019-11-28 11:33:30
I'm facing this issue when i try to download and install a package from git-hub using devtools. R Version : 3.1.3 (64 bit) > install_github("hadley/httr") Downloading github repo hadley/httr@master Error in curl::curl_fetch_memory(url, handle = handle) : Timeout was reached > traceback() 13: .Call(R_curl_fetch_memory, url, handle) 12: curl::curl_fetch_memory(url, handle = handle) 11: request_fetch.write_memory(req$output, req$url, handle) 10: request_fetch(req$output, req$url, handle) 9: request_perform(req, hu$handle$handle) 8: httr::HEAD(src_submodules, , auth) 7: github_has_remotes(x, auth)

Error while using install_github | devtools | timeout issue

由 大兔子大兔子 提交于 2019-11-27 19:20:30
问题 I'm facing this issue when i try to download and install a package from git-hub using devtools. R Version : 3.1.3 (64 bit) > install_github("hadley/httr") Downloading github repo hadley/httr@master Error in curl::curl_fetch_memory(url, handle = handle) : Timeout was reached > traceback() 13: .Call(R_curl_fetch_memory, url, handle) 12: curl::curl_fetch_memory(url, handle = handle) 11: request_fetch.write_memory(req$output, req$url, handle) 10: request_fetch(req$output, req$url, handle) 9:

Linking Intel's Math Kernel Library (MKL) to R on Windows

由 随声附和 提交于 2019-11-27 13:43:54
问题 Using an alternative BLAS for R has several advantages, see e.g. https://cran.r-project.org/web/packages/gcbd/vignettes/gcbd.pdf. Microsoft R Open https://mran.revolutionanalytics.com/documents/rro/installation/#sysreq is using Intel's MKL instead of the default Reference BLAS to speed up calculations. My question is: What would be the exact steps to link Intel's MKL library **manually to R**'s most recent version on Windows (https://cran.r-project.org/bin/windows/base/)? UPDATE 20-07-2016:
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