I ran some experiments using CreateDataPartition in R to split the train and test data. I looped the results over about 500 times and did it on one laptop. When I tried to replicate the experiments on another laptop with the same code and data, it gave me very different results and not close to what I had before. I assume that this could be due to the seed issue and I am trying to figure out how to manage this so that I can replicate at least almost the same results as before. Any suggestions?
Below is a snapshot of how I am splitting the train and test data:
for (i in 1:500){
set.seed(i)
index = createDataPartition(data$S, p=.75,list=FALSE,times=1)
train = data[index,]
test= data[-index,]