I am trying to fit a model with the SuperLearner package. However, I can't even get past the stage of playing with the package to get comfortable with it....
I use the following code:
superlearner<-SuperLearner::SuperLearner(Y=y, X=as.data.frame(data_train[1:30]), family =binomial(), SL.library = list("SL.glmnet"), obsWeights = weights)
y is a numeric vector of the same length as my dataframe "data_train", containing the correct labels with 9 different classes. The dataframe "data_train" contains 30 columns with numeric data.
When i run this, i get the Error:
Error in get(library$screenAlgorithm[s], envir = env) :
Objekt 'All' not found
I don't really know what the problem could be and i can't really wrap my head around the source code. Please note that the variable obsWeights in the function contains a numeric vector of the same length as my data with weights i calculated for the model. This shouldn't be the problem, as it doesn't work either way.
Unfortunately i can't really share my data on here, but maybe someone had this error before...
Thanks!
this seems to happen if you do not attach SuperLearner, you can fix via library(SuperLearner)
Related
Possibly it's a stupid question (but be patient, I'm a beginner in R's word)... I'm working with ImpulseDE2, a package designed to RNAseq data analysis along different times (see article for more information).
The running function (runImpulseDE2) requires a matrix counts and a annotation data frame. I've created both but it appears this error message:
Error in checkCounts(matCountData, "matCountData"): ERROR: matCountData contains non-integer elements. Requires count data.
I have tried some solutions and nothing seems to work (and I've not found any solution in the Internet)...
as.matrix(data)
(data + 1) > and there isn't NAs nor zero values that originate this error ($ which(is.na(data)) and $ which(data < 1), but both results are integer(0))
as.numeric(data) > and appears another error: ERROR: [Rownames of matCountData] was not given as input.
I think that's something I'm not realizing, but I'm totally locked. Every tip will be welcome!
And here is the (silly) solution! This function seems not to accept float numbers... so applying a simple round is enough to solve this error.
Thanks for your help!
I'm using the mice package to interpolate some missing values. I've successfully been using mice in many cases without any problem. However I am now facing an unprecedented problem, that is, after the first iteration I get the following error:
mice(my_data)
iter imp variable
1 1 sunlight
Show Traceback
Rerun with Debug
Error in cor(xobs[, keep, drop = FALSE], use = "all.obs") : 'x' is empty
I have tried to look in the documentation but I cannot find anything useful. I looked up the error on the internet and found this https://stat.ethz.ch/pipermail/r-help/2015-December/434914.html but I was unable to find the answer to the problem described.
Sadly I cannot provide a working example of the data since my_data contains private data that I do not own and therefore cannot make publicly available. my_data is a dplyr dataframe however it looks like there's no difference in using a dplyr or a "base" dataframe.
Could anyone please explain me what is happening and (possibly) how to fix it? Thank you.
EDIT: added some more info on traceback:
cor(xobs[, keep, drop = FALSE], use = "all.obs")
4 remove.lindep(x, y, ry, ...)
3 sampler(p, data, m, imp, r, visitSequence, c(from, to), printFlag,
...)
2 mice::mice(my_data)
Very possible, some columns in the data input are overly correlated that certain methods of imputation are not applicable.
I have a file that I formatted for ANOVA but for I cannot run the function boxplot nor aov on it. It can be downloaded from this link:
When running "boxplot(AnovaPolyg.boxplot(AnovaPolyg...Sheet1$Frequency~AnovaPolyg...Sheet1$Race)..Sheet1$Frequency~AnovaPolyg...Sheet1$Race)
or
anov.aov=aov(AnovaPolyg...Sheet1$Race~AnovaPolyg...Sheet1$Frequency)
I get the following error:
Error in boxplot.default(split(mf[[response]], mf[-response]), ...) :
adding class "factor" to an invalid object
Can someone please check the data file and tell me if they spot the problem?
I don't follow your examples, but I think the issue could be when you read in the data, it is treating Frequency as a factor. This is because on line 25838, the entry is 0,1 instead of 0.1. Fix this, read the data back in, check to make sure it's numeric (str will help with this), and you should be good to go.
I just the same error when i tried to do boxplot between two binary variables. Instead when tried for boxplot between one binary and one scale variable, error is gone. Just my thoughts.
I am conducting a sensitivity study using the Sensitivity package. When trying to calculate the sensitivity indices with the output data of the external model I get the error specified in the titel.
The output is a three column table stored in a csv file which I read in as follows:
day1 <- read.csv("day_1_outputs.csv",header=FALSE)
Now when I try to calculate sensitivity indices with the ouput of the first column:
tell(sob.pars,day1[,1])
I get:
Error in `row.names<-.data.frame`(`*tmp*`, value = value) :
invalid 'row.names' length
At first I thought I should use a matrix like object because in another study I conducted I generated the ouput from a raster image read in as a matrix which worked fine, but that didn't help.
The help page for tell states using a vector for the model results but even if I store the column of the dataframe before using tell the problem persists.
I guess my main problem is that I don't understand the error message in conjunction with the tell function, sob.pars is a list returned by sensitivity analyses objects constructors from the same package so I don't know to which rownames of that object the message is refering.
Any hint is appreciated.
Finally found out what the problem was. The error is kind of missleading.
The problem was not the row names since these were identical, that's what irritated me in the first place. There was obviously nothing wrong with them.
The actual problem was the column names in sob.pars. These were missing. Once I added these everything worked fine. Thanks rawr anyways (I just only now noticed someone had commented on the question, I thought I would be notified when this happens, but I guess not).
I'm trying to understand what a particular error message means in R.
I'm using an ff data frame (ffdf) to build an rpart model. That works fine.
However, when I try to apply the predict function (or any function) using ffdfdply, I get a cryptic error message that I can't seem to crack. I'm hoping someone here can shed light on its meaning.
PredictedData<-ffdfdply(x=TrainingData,split=TrainingData$id,
FUN=function(x) {x$Predicted<-predict(Model1,newdata=x)
x})
If I've thought about this correctly, ffdfdply will take the TrainingData table, split it into chunks based on TrainingData$id, then apply the predict function using the model file Model1. Then it will return the table (its labelled x in the function field), combine them back together into the table PredictedData. PredictedData should be the same as TrainingData, except with an additional column called "Predicted" added.
However, when I run this, I get rather unhelpful error message.
2014-07-16 21:16:17, calculating split sizes
2014-07-16 21:16:36, building up split locations
2014-07-16 21:17:02, working on split 1/30, extracting data in RAM of 32 split elements, totalling, 0.07934 GB, while max specified data specified using BATCHBYTES is 0.07999 GB
Error: is.null(names(x)) is not TRUE
In addition: Warning message:
In ffdfdply(x = TrainingData, split = TrainingData$id, FUN = function(x) { :
split needs to be an ff factor, converting using as.character.ff to an ff factor
Yes, every column has a name. Those names contain just alphanumeric characters plus periods. But the error message makes me think that that the columns should not have names? I guess I 'm confused what this means exactly.
I appreciate any hints anyone can provide and I'll be happy to provide more detail.
I think I found the solution to this.
Turns out I had periods in my column names. When I removed those periods, this worked perfectly.