One easy way to run fully reproducible model in parallel mode using the caret package is by using the seeds argument when calling the train control. Here the above question is resolved, check the trainControl help page for further infos. library(doParallel); library(caret) #create a list of seed, here change the seed for each resampling set.seed(123) … Read more
In tensorflow, a random operation relies on two different seeds: a global seed, set by tf.set_random_seed, and an operation seed, provided as an argument to the operation. You will find more details on how they relate in the docs. You have a different seed for each random op because each random op maintains its own … Read more
Using the iris dataset, which is handily included into R, we can see how dput() works: data(iris) head(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 … Read more