microsoft-r

问题 I am running ML server and I have a service deployed that expects one of its inputs to be a data.frame. When I connect with R to that API endpoint using mrsdeploy, I am able to pass a data.frame. I would like to do the same in prostman using json. How can I format my json for lets say an input (data.frame) of characteristics about someone? I would assume its something like { ... "bio": { "age" : 23, "height" : 12, "eyeC" : "red" } } I have tried a variety of combinations all getting back an

问题 I was doing some principal component analysis on my macbook running Microsoft R 3.3.0 when I got some strange results. Double checking with a colleague, I've realised that the output of the SVD function was different from what I may get by using vanilla R. This is the reproducible result, please load the file (~78 Mb) here With Microsoft R 3.3.0 (x86_64-apple-darwin14.5.0) I get: >> sv <- svd(Cx) >> print(sv$d[1:10]) [1] 122.73664 104.45759 90.52001 87.21890 81.28256 74.33418 73.29427 66

问题 I've never had any issues installing packages on R, but I always have issues installing packages on Microsoft R Open. For example, I attempted to install tidyverse. I received many errors, listed below: > Warning in system(cmd) : error in running command ERROR: compilation > failed for package ‘colorspace’ > * removing ‘/home/myFilePath/R/x86_64-pc-linux-gnu-library/3.5/colorspace’ > Warning in install.packages : installation of package ‘colorspace’ > had non-zero exit status > * installing

问题 I've never had any issues installing packages on R, but I always have issues installing packages on Microsoft R Open. For example, I attempted to install tidyverse. I received many errors, listed below: > Warning in system(cmd) : error in running command ERROR: compilation > failed for package ‘colorspace’ > * removing ‘/home/myFilePath/R/x86_64-pc-linux-gnu-library/3.5/colorspace’ > Warning in install.packages : installation of package ‘colorspace’ > had non-zero exit status > * installing

问题 I am currenlty computing glm models off a huge data data set. Both glm and even speedglm take days to compute. I currently have around 3M observations and altogether 400 variables, only some of which are used for the regression. In my regression I use 4 integer independent variables ( iv1 , iv2 , iv3 , iv4 ), 1 binary independent variable as factor ( iv5 ), the interaction term ( x * y , where x is an integer and y is a binary dummy variable as factor). Finally, I have fixed effects along

问题 I need to run a logistic regression on a relatively large data frame with 480.000 entries with 3 fixed effect variables. Fixed effect var A has 3233 levels, var B has 2326 levels, var C has 811 levels. So all in all I have 6370 fixed effects. The data is cross-sectional. If I can't run this regression using the normal glm function because the regression matrix seems too large for my memory (I get the message " Error: cannot allocate vector of size 22.9 Gb "). I am looking for alternative ways

问题 I have a for loop that usually writes to a flat file. This way, if anything breaks, I can start where I left off. I want to convert this process to read and write from a SQL table directly using the new RevoScaleR functions in a SQL Server 2016 stored procedure that executes my R code. Here is a simple SPROC: USE [master] GO /****** Object: StoredProcedure [dbo].[Rscript_geocodeUSACities_TEST] Script Date: 8/8/2017 11:40:40 AM ******/ SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO CREATE

问题 recently I installed Microsoft R Open 3.3.1 on my MacBook Pro (El Capitan 10.11.6). When I open RStudio or I use the R console I get this warning message: Warning message: In doTryCatch(return(expr), name, parentenv, handler) : unable to load shared object '/Library/Frameworks/R.framework/Resources/modules//R_X11.so': dlopen(/Library/Frameworks/R.framework/Resources/modules//R_X11.so, 6): Symbol not found: _CGBitmapContextCreate Referenced from: /Library/Frameworks/R.framework/Resources

问题 Why does the following MSR code not replace the original column "Var1"? rxDataStep(inData = input_xdf, outFile = input_xdf, overwrite = TRUE, transforms = list(Var1 = as.numeric(Var1)), transformVars = c("Var1") ) 回答1: At the moment, RevoScaleR doesn't support changing the type of a variable in an xdf file (even if you write to a different file). The way to do it is to create a new variable, drop the old, and then rename the new variable to the old name. I would suggest doing this with a

问题 Is it possible to split a .xdf file in (the Microsoft RevoScaleR context) into a let's say 75% training and 25% test set? I know there is a function called rxSplit(), but, the documentation doesn't seem to apply to this case. Most of the examples online assign a column of random numbers to the dataset, and split it using that column. Thanks. Thomas 回答1: You can certainly use rxSplit for this. Create a variable that defines your training and test samples, and then split on it. For example,