For a research project, I conducted the following methodology. The dataset was of size $N$.
$B$ times, I:
took a random $N/2$ rows and trained my model, which finds the optimal size $M$ of a system of resources
took the other half of the rows, the other $N/2$, and simulated the system assuming the size of the system was $M$. This led to a performance metric I will denote $E$.
I then reported the mean and confidence interval of $E$ across all $B$ iterations.
My questions are:
- Is this bootstrapping without replacement or "repeated 2-fold cross validation"?
- If the answer is both, what exactly is the difference between bootstrapping without replacement and "repeated cross validation"?
My methodology is summarized in this wikipedia, but strangely it is not called bootstrapping, but I thought this was bootstrapping, hence my confusion: http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29#Repeated_random_sub-sampling_validation