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
You can certainly use rxSplit for this. Create a variable that defines your training and test samples, and then split on it.
For example, using the mtcars toy dataset:
xdf <- rxDataStep(mtcars, "mtcars.xdf")
xdfList <- rxSplit(xdf, splitByFactor="test",
transforms=list(test=factor(runif(.rxNumRows) < 0.25, levels=c("FALSE", "TRUE"))))
xdfList is now a list containing 2 xdf data sources: one with (approximately) 75% of the data, and the other with 25%.
You can use rxDataStep to create the training and testing data sets from the original xdf. Check out this example: https://docs.microsoft.com/en-us/r-server/r/how-to-revoscaler-linear-model
bigDataDir <- "C:/MRS/Data"
sampleAirData <- file.path(bigDataDir, "AirOnTime7Pct.xdf")
trainingDataFile <- "AirlineData06to07.xdf"
targetInfile <- "AirlineData08.xdf"
rxDataStep(sampleAirData, trainingDataFile, rowSelection = Year == 1999 |
Year == 2000 | Year == 2001 | Year == 2002 | Year == 2003 |
Year == 2004 | Year == 2005 | Year == 2006 | Year == 2007)
rxDataStep(sampleAirData, targetInfile, rowSelection = Year == 2008)
